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Microsoft Azure Training

accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (1 days)

Online Self-paced (8 hours)

AZ-900: Microsoft Azure Fundamentals

Microsoft Azure Fundamentals AZ900 Course Outline

Within this Microsoft training course, you will learn the following modules:

Module 1: Cloud Concepts

In this module, you'll take an entry level end-to-end look at cloud concepts, which will provide you with a solid foundation for completing the available modules for Azure Fundamentals.

Lessons

  • Cloud Computing
  • Cloud benefits
  • Cloud service types

After completing this module, students will be able to:

  • Describe cloud computing.
  • Describe the benefits of using cloud services.
  • Describe cloud service types.

Module 2: Azure Architecture and Services

This module explores Microsoft Azure, its architecture, and some of the most used services and resources.

Lessons

  • Core Azure architectural components
  • Azure compute and networking services
  • Azure storage services
  • Azure identity, access, and security

Lab: Explore the Microsoft Learn sandbox

Lab: Create an Azure resource

Lab: Create an Azure virtual machine

Lab: Configure network access

Lab: Create a storage blob

After completing this module, students will be able to:

  • Describe the core architectural components of Azure.
  • Describe Azure compute and networking services.
  • Describe Azure storage services.
  • Describe Azure identity, access, and security.

Module 3: Core Solutions

In this module, you'll learn about the management and governance resources available to help you manage your cloud and on-premises resources.

Lessons

  • Cost management in Azure
  • Features and tools in Azure for governance and compliance
  • Feature and tools for managing and deploying Azure resources
  • Monitoring tools in Azure

Lab: Configure a resource lock

Lab: Compare workload costs using the Total Cost of Ownership calculator

Lab: Estimate workload costs using the Pricing calculator

After completing this module, students will be able to:

  • Describe cost management in Azure.
  • Describe features and tools in Azure for governance and compliance.
  • Describe features and tools for managing and deploying Azure resources.
  • Describe monitoring tools in Azure.

Please note the exam is not included in the cost of this course.

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Who should attend this Microsoft training course?

This course is suitable for IT personnel who are just beginning to work with Azure. This audience wants to learn about our offerings and get hands-on experience with the product. This course primarily uses the Azure portal and command line interface to create resources and does not require scripting skills. Students in this course will gain confidence to take other role-based courses and certifications, such as Azure Administrator. This course combines lecture, demonstrations, and hands-on labs. This course will also help prepare someone for the AZ-900 exam.

  • Job role: Administrator
  • Preparation for exam: AZ-900

Prerequisites

There are no prerequisites for taking this course. Familiarity with cloud computing is helpful but isn't necessary.

 

Please note the exam is not included in the cost of this course.

Microsoft Azure Fundamentals AZ900 Course Overview

This course will provide foundational level knowledge on cloud concepts; core Azure services; and Azure management and governance features and tools. Azure Fundamentals exam is an opportunity to prove knowledge of cloud concepts, Azure services, Azure workloads, security, and privacy in Azure, as well as Azure pricing and support. Candidates should be familiar with the general technology concepts, including concepts of networking, storage, compute, application support, and application development.

What delegate will gain from this Microsoft Azure Fundamentals Training Course:

  • To be able to describe cloud concepts.
  • To be able to describe Azure architecture and services.
  • To be able to describe Azure management and governance.

Please note the exam is not included in the cost of this course.

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What's included within this Microsoft training course?

  • Experienced tutor
  • Microsoft Labs

Please note the exam is not included in the cost of this course.

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Microsoft Azure Fundamentals Exam Information | AZ900

Please note the exam is not included in the cost of this course. 

The Microsoft Certified Azure Fundamentals exam measures your ability to understand cloud concepts, core Azure Services, Azure pricing and support, and the fundamentals of cloud security, privacy, compliance, and trust. It measures the following areas:

  • Describe cloud concepts (25–30%)
  • Describe Azure architecture and services (35–40%)
  • Describe Azure management and governance (30–35%)

All technical exam scores are reported on a scale 1 to 1,000. A passing score is 700 or greater. 

Please note the exam is not included in the cost of this course.

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accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Microsoft Azure Data Fundamentals DP900 Course Outline

Within his Microsoft training course, you will learn the following modules:

Module 1: Explore core data concepts

Students will learn about core data concepts such as common data formats, workloads, and roles, and build their foundational knowledge of cloud data services within Microsoft Azure.

Lessons

  • Core data concepts
  • Data roles and Services

After completing this module, students will be able to:

  • Identify common data formats
  • Describe options for storing data in files
  • Describe options for storing data in databases
  • Describe characteristics of transactional data processing solutions
  • Describe characteristics of analytical data processing solutions
  • Identify common data professional roles
  • Identify common cloud services used by data professionals

Module 2: Explore fundamentals of relational data in Azure

Students will explore fundamental relational data concepts and relational database services in Azure.

Lessons

  • Explore relational data offerings in Azure
  • Explore Azure services for relational data

Lab: Provision Azure relational database services

After completing this module, students will be able to:

  • Identify characteristics of relational data
  • Define normalization
  • Identify types of SQL statement
  • Identify common relational database objects
  • Identify options for Azure SQL services
  • Identify options for open-source databases in Azure
  • Provision a database service on Azure

Module 3: Explore fundamentals of non-relational data in Azure

Students will explore Azure storage for non-relational data and the fundamentals of Azure Cosmos DB.

Lessons

  • Fundamentals of Azure Storage
  • Fundamentals of Azure Cosmos DB

Lab: Explore Azure Storage

Lab: Explore Azure Cosmos DB

After completing this module, students will be able to:

  • Describe features and capabilities of Azure blob storage
  • Describe features and capabilities of Azure Data Lake Gen2
  • Describe features and capabilities of Azure file storage
  • Describe features and capabilities of Azure table storage
  • Provision and use an Azure Storage account
  • Describe key features and capabilities of Azure Cosmos DB
  • Identify the APIs supported in Azure Cosmos DB
  • Provision and use an Azure Cosmos DB instance

Module 4: Explore fundamentals of data analytics

Students will learn about large-scale data warehousing, real-time analytics, and data visualization.

Lessons

  • Large-scale data warehousing
  • Streaming and real-time analytics
  • Data visualization

Lab: Analyze streaming data

Lab: Visualize data with Power BI

Lab: Explore Azure Synapse Analytics

After completing this module, students will be able to:

  • Identify common elements of a large-scale data warehousing solution
  • Describe key features for data ingestion pipelines
  • Identify common types of analytical data store and related Azure services
  • Provision Azure Synapse Analytics and use it to ingest, process, and query data
  • Compare batch and stream processing
  • Describe common elements of streaming data solutions
  • Describe features and capabilities of Azure Stream Analytics
  • Describe features and capabilities of Spark Structured Streaming on Azure
  • Describe features and capabilities of Azure Synapse Data Explorer
  • Describe a high-level process for creating reporting solutions with Microsoft Power BI
  • Describe core principles of analytical data modeling
  • Identify common types of data visualization and their uses
  • Create an interactive report with Power BI Desktop

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Who should attend this Microsoft training course?

The audience for this course is individuals who want to learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure.

  • Job role: Data Engineer
  • Preparation for exam: DP-900

Prerequisites

Prerequisite certification is not required before taking this course. Successful Azure Data Fundamentals students start with some basic awareness of computing and Internet concepts, and an interest in extracting insights from data.

Specifically:

  • Experience using a web browser, such as Microsoft Edge.
  • Familiarity with basic data-related concepts, such as working with tables of data in a spreadsheet and visualizing data using charts.
  • A willingness to learn through hands-on exploration.

Microsoft Azure Data Fundamentals DP900 Course Overview

In this course, students will gain foundational knowledge of core data concepts and related Microsoft Azure data services. Students will learn about core data concepts such as relational, non-relational, big data, and analytics, and build their foundational knowledge of cloud data services within Microsoft Azure. Students will explore fundamental relational data concepts and relational database services in Azure. They will explore Azure storage for non-relational data and the fundamentals of Azure Cosmos DB. Students will learn about large-scale data warehousing, real-time analytics, and data visualization.

What will you gain from taking this Microsoft training course?

  • Describe core data concepts.
  • Identify considerations for relational data on Azure.
  • Describe considerations for working with non-relational data on Azure.
  • Describe an analytics workload on Azure.

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What's included within this Microsoft training course?

  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

Show moredown

accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Microsoft Azure AI Fundamentals AI900 Course Outline

Within this Microsoft training course, you will learn the following modules:

Module 1: Explore Fundamentals of Artificial Intelligence

In this module, you'll learn about common uses of artificial intelligence (AI), and the several types of workloads associated with AI. You'll then explore considerations and principles for responsible AI development.

Lessons

  • Introduction to Artificial Intelligence
  • Artificial Intelligence in Microsoft Azure

After completing this module, students will be able to:

  • Describe Artificial Intelligence workloads and considerations

Module 2: Explore Fundamentals of Machine Learning

Machine learning is the foundation for modern AI solutions. In this module, you'll learn about some fundamental machine learning concepts, and how to use the Azure Machine Learning service to create and publish machine learning models.

Lessons

  • Introduction to Machine Learning
  • Azure Machine Learning

After completing this module, students will be able to:

  • Describe fundamental principles of machine learning on Azure

Module 3: Explore Fundamentals of Computer Vision

Computer vision is the area of AI that deals with understanding the world visually, through images, video files, and cameras. In this module you'll explore multiple computer vision techniques and services.

Lessons

  • Computer Vision Concepts
  • Creating Computer Vision solutions in Azure

After completing this module, students will be able to:

  • Describe features of computer vision workloads on Azure

Module 4: Explore Fundamentals of Natural Language Processing

This module describes scenarios for AI solutions that can process written and spoken language. You'll learn about Azure services that can be used to build solutions that analyze text, recognize, and synthesize speech, translate between languages, and interpret commands.

Lessons

  • Introduction to Natural Language Processing
  • Building Natural Language Solutions in Azure

After completing this module, students will be able to:

  • Describe features of Natural Language Processing (NLP) workloads on Azure

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Who should attend this Microsoft training course?

The Azure AI Fundamentals course is designed for anyone interested in learning about the types of solution artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You don’t need to have any experience of using Microsoft Azure before taking this course, but a basic level of familiarity with computer technology and the Internet is assumed. Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret charts. The course includes hands-on activities that involve working with data and running code, so a knowledge of fundamental programming principles will be helpful.

  • Job role: AI Engineer
  • Preparation for exam: AI-900

Prerequisites

Prerequisite certification is not required before taking this course. Successful Azure AI Fundamental students start with some basic awareness of computing and internet concepts, and an interest in using Azure AI services.

Specifically:

  • Experience using computers and the internet.
  • Interest in use cases for AI applications and machine learning models.
  • A willingness to learn through hands-on exploration.

Microsoft Azure AI Fundamentals AI900​ Course Overview

Microsoft Azure is a growing collection of cloud services to support organisations to meet their market challenges. It facilitates to maintain and use applications on an extensive global network by utilising their frameworks and tools. AI (Artificial Intelligence) is a computing system that improves with experience. AI can also be defined as a method of converting data into the software. Microsoft Azure Artificial Intelligence (AI) is a service that a developer can utilise to create predictive analytics models and then quickly use those models for consumption as cloud web services. The Microsoft Azure AI Fundamentals is one of the most demanded training programs broadly used by organisations who want to train their employees for the fundamental concepts of AI (Artificial intelligence), ML (Machine Learning) and related Azure services.

In this 1-day Microsoft Azure AI Fundamentals training course, delegates will gain knowledge about necessary uses of AI (Artificial Intelligence) and the various kinds of the workload associated with AI. Delegates will get to know about some fundamental machine learning concepts, and how to utilise the Azure Machine Learning service to design and issue machine learning models. They will become familiar with the features of computer vision workloads on Azure. Our expert trainers of The Knowledge Academy, who have years of experience in this field, will teach this course.

This training will cover various essential concepts, such as: 

  • Artificial intelligence in Azure
  • Azure machine learning
  • Computer vision concepts
  • Conversational AI
  • Natural Language Processing (NLP)

At the end of Microsoft Azure AI Fundamentals training course, delegates will know how to use the Azure machine learning service to create and publish machine learning models. Delegates will become able to explore multiple computer vision techniques, services, and features of NLP (Natural Language Processing) workloads on Azure.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

Show moredown

accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (5 days)

Online Self-paced (40 hours)

Developing Solutions for Microsoft Azure AZ204 Course Outline

Within this training course you will learn the following modules: 

Module 1: Create Azure App Service web apps

Learn how Azure App Service functions and how to create and update an app. Explore App Service authentication and authorization, configuring app settings, scale apps, and how to use deployment slots.

Lessons

  • Explore Azure App Service
  • Configure web app settings
  • Scale apps in Azure App Service
  • Explore Azure App Service deployment slots

Module 2: Implement Azure functions

Learn how to create and deploy Azure Functions. Explore hosting options, bindings, triggers, and how to use Durable Functions to define stateful workflows.

Lessons

  • Explore Azure Functions
  • Develop Azure Functions
  • Implement Durable Functions

Module 3: Develop solutions that use Blob storage

Learn how to create Azure Blob storage resources, manage data through the blob storage lifecycle, and work with containers and items by using the Azure Blob storage client library V12 for .NET.

Lessons

  • Explore Azure Blob storage
  • Manage the Azure Blob storage lifecycle
  • Work with Azure Blob storage

Module 4: Develop solutions that use Azure Cosmos DB

Learn how to create Azure Cosmos DB resources with the appropriate consistency levels, choose and create a partition key, and perform data operations by using the .NET SDK V3 for Azure Cosmos DB.

Lessons

  • Explore Azure Cosmos DB
  • Implement partitioning in Azure Cosmos DB
  • Work with Azure Cosmos DB

Module 5: Implement infrastructure as a service solution

Learn how to create and deploy virtual machine, deploy resources using Azure Resource Manager templates, and manage and deploy containers.

Lessons

  • Provision virtual machines in Azure
  • Create and deploy Azure Resource Manager templates
  • Manage container images in Azure Container Registry
  • Run container images in Azure Container Instances

Module 6: Implement user authentication and authorization

Learn how to implement authentication and authorization to resources by using the Microsoft identity platform, Microsoft Authentication Library, shared access signatures, and use Microsoft Graph.

Lessons

  • Explore the Microsoft identity platform
  • Implement authentication by using the Microsoft Authentication Library
  • Implement shared access signatures
  • Explore Microsoft Graph

Module 7: Implement secure cloud solutions

Learn how to deploy apps more securely in Azure by using Azure Key Vault, managed identities, and Azure App Configuration.

Lessons

  • Implement Azure Key Vault
  • Implement managed identities
  • Implement Azure App Configuration

Module 8: Implement API Management

Learn how the API Management service functions, how to transform and secure APIs, and how to create a backend API.

Lessons

  • Explore API Management

Module 9: Develop event-based solutions

Learn how to build applications with event-based architectures by integrating Azure Event Grid and Azure Event Hubs into your solution.

Lessons

  • Explore Azure Event Grid
  • Explore Azure Event Hubs

Module 10: Develop message-based solutions

Learn how to build applications with message-based architectures by integrating Azure Service Bus and Azure Queue Storage into your solution.

Lessons

  • Discover Azure message queues

Module 11: Instrument solutions to support monitoring and logging

Learn how to instrument apps to enable Application Insights to monitor performance and help troubleshoot issues.

Lessons

  • Monitor app performance

Module 12: Integrate caching and content delivery within solutions

Learn how to improve the performance and scalability of your applications by integrating Azure Cache for Redis and Azure Content Delivery Network into your solution.

Lessons

  • Develop for Azure Cache for Redis
  • Develop for storage on CDNs

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Who should attend this Microsoft training course?

Students in this course are interested in Azure development or in passing the Microsoft Azure Developer Associate certification exam.

  • Job role: Developer
  • Preparation for exam: AZ-204

Microsoft prerequisites

To be successful in this course, learners should have the following:

  • Hands-on experience with Azure IaaS and PaaS solutions, and the Azure Portal.
  • Experience writing in an Azure supported language at the intermediate level. (C#, JavaScript, Python, or Java)
  • Ability to write code to connect and perform operations on, a SQL or NoSQL database product. (SQL Server, Oracle, MongoDB, Cassandra or similar)
  • Experience writing code to handle authentication, authorization, and other security principles at the intermediate level.
  • A general understanding of HTML, the HTTP protocol and REST API interfaces.

Developing Solutions for Microsoft Azure AZ204 Course Overview

his course teaches developers how to create end-to-end solutions in Microsoft Azure. Students will learn how to implement Azure compute solutions, create Azure Functions, implement, and manage web apps, develop solutions utilizing Azure storage, implement authentication and authorization, and secure their solutions by using KeyVault and Managed Identities. Students will also learn how to connect to and consume Azure services and third-party services and include event- and message-based models in their solutions. The course also covers monitoring, troubleshooting, and optimizing Azure solutions.

 

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What's included within this Microsoft training course?

  • Experienced Tutor

Show moredown

accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (4 days)

Online Self-paced (32 hours)

Designing and Implementing Microsoft DevOps solutions AZ400 Course Outline

Within this Microsoft training course, you will learn the following modules:

Module 1: Get started on a DevOps transformation journey

Lessons

  • Introduction to DevOps
  • Choose the right project
  • Describe team structures
  • Choose the DevOps tools
  • Plan Agile with GitHub Projects and Azure Boards
  • Introduction to source control
  • Describe types of source control systems
  • Work with Azure Repos and GitHub

Lab: Agile planning and portfolio management with Azure Boards

Lab: Version controlling with Git in Azure Repos

After completing this module, students will be able to:

  • Understand what DevOps is and the steps to accomplish it
  • Identify teams to implement the process
  • Plan for the transformation with shared goals and timelines
  • Plan and define timelines for goals
  • Understand different projects and systems to guide the journey
  • Select a project to start the DevOps transformation
  • Identify groups to minimize initial resistance
  • Identify project metrics and Key Performance Indicators (KPI's)
  • Understand agile practices and principles of agile development
  • Create a team and agile organizational structure

Module 2: Development for enterprise DevOps

Lessons

  • Structure your Git Repo
  • Manage Git branches and workflows
  • Collaborate with pull requests in Azure Repos
  • Explore Git hooks
  • Plan foster inner source
  • Manage Git repositories
  • Identify technical debt

Lab: Version controlling with Git in Azure Repos

After completing this module, students will be able to:

  • Understand Git repositories
  • Implement mono repo or multiple repos
  • Explain how to structure Git Repos
  • Implement a change log
  • Describe Git branching workflows
  • Implement feature branches
  • Implement GitFlow
  • Fork a repo
  • Leverage pull requests for collaboration and code reviews
  • Give feedback using pull requests

Module 3: Implement CI with Azure Pipelines and GitHub Actions

Lessons

  • Explore Azure Pipelines
  • Manage Azure Pipeline agents and pools
  • Describe pipelines and concurrency
  • Explore Continuous integration
  • Implement a pipeline strategy
  • Integrate with Azure Pipelines
  • Introduction to GitHub Actions
  • Learn continuous integration with GitHub Actions
  • Design a container build strategy

Lab: Configuring agent pools and understanding pipeline styles

Lab: Enabling continuous integration with Azure Pipelines

Lab: Integrating external source control with Azure Pipelines

Lab: Implementing GitHub Actions by using DevOps Starter

Lab: Deploying Docker Containers to Azure App Service web apps

After completing this module, students will be able to:

  • Describe Azure Pipelines
  • Explain the role of Azure Pipelines and its components
  • Decide Pipeline automation responsibility
  • Understand Azure Pipeline key terms
  • Choose between Microsoft-hosted and self-hosted agents
  • Install and configure Azure pipelines Agents
  • Configure agent pools
  • Make the agents and pools secure
  • Use and estimate parallel jobs

Module 4: Design and implement a release strategy

Lessons

  • Introduction to continuous delivery
  • Create a release pipeline
  • Explore release strategy recommendations
  • Provision and test environments
  • Manage and modularize tasks and templates
  • Automate inspection of health

Lab: Creating a release dashboard

Lab: Controlling deployments using Release Gates

After completing this module, students will be able to:

  • Explain continuous delivery (CD)
  • Implement continuous delivery in your development cycle
  • Understand releases and deployment
  • Identify project opportunities to apply CD
  • Explain things to consider when designing your release strategy
  • Define the components of a release pipeline and use artifact sources
  • Create a release approval plan
  • Implement release gates
  • Differentiate between a release and a deployment

Module 5: Implement a secure continuous deployment using Azure Pipelines

Lessons

  • Introduction to deployment patterns
  • Implement blue-green deployment and feature toggles
  • Implement canary releases and dark launching
  • Implement A/B testing and progressive exposure deployment
  • Integrate with identity management systems
  • Manage application configuration data

Lab: Configuring pipelines as code with YAML

Lab: Setting up and running functional tests

Lab: Integrating Azure Key Vault with Azure DevOps

After completing this module, students will be able to:

  • Explain the terminology used in Azure DevOps and other Release Management Tooling
  • Describe what a Build and Release task is, what it can do, and some available deployment tasks
  • Implement release jobs
  • Differentiate between multi-agent and multi-configuration release job
  • Provision and configure target environment
  • Deploy to an environment securely using a service connection
  • Configure functional test automation and run availability tests
  • Setup test infrastructure
  • Use and manage task and variable groups

Module 6: Manage infrastructure as code using Azure and DSC

Lessons

  • Explore infrastructure as code and configuration management
  • Create Azure resources using Azure Resource Manager templates
  • Create Azure resources by using Azure CLI
  • Explore Azure Automation with DevOps
  • Implement Desired State Configuration (DSC)
  • Implement Bicep

Lab: Azure deployments using Azure Resource Manager templates

After completing this module, students will be able to:

  • Understand how to deploy your environment
  • Plan your environment configuration
  • Choose between imperative versus declarative configuration
  • Explain idempotent configuration
  • Create Azure resources using ARM templates
  • Understand ARM templates and template components
  • Manage dependencies and secrets in templates
  • Organize and modularize templates
  • Create Azure resources using Azure CLI

Module 7: Implement security and validate code bases for compliance

Lessons

  • Introduction to Secure DevOps
  • Implement open-source software
  • Software Composition Analysis
  • Static analyzers
  • OWASP and Dynamic Analyzers
  • Security Monitoring and Governance

Lab: Implement security and compliance in Azure Pipelines

Lab: Managing technical debt with SonarQube and Azure DevOps

After completing this module, students will be able to:

  • Identify SQL injection attack
  • Understand DevSecOps
  • Implement pipeline security
  • Understand threat modeling
  • Implement open-source software
  • Explain corporate concerns for open-source components
  • Describe open-source licenses
  • Understand the license implications and ratings
  • Work with Static and Dynamic Analyzers
  • Configure Microsoft Defender for Cloud

Module 8: Design and implement a dependency management strategy

Lessons

  • Explore package dependencies
  • Understand package management
  • Migrate, consolidate, and secure artifacts
  • Implement a versioning strategy
  • Introduction to GitHub Packages

Lab: Package management with Azure Artifacts

After completing this module, students will be able to:

  • Define dependency management strategy
  • Identify dependencies
  • Describe elements and componentization of a dependency management
  • Scan your codebase for dependencies
  • Implement package management
  • Manage package feed
  • Consume and create packages
  • Publish packages
  • Identify artifact repositories
  • Migrate and integrate artifact repositories

Module 9: Implement continuous feedback

Lessons

  • Implement tools to track usage and flow
  • Develop monitor and status dashboards
  • Share knowledge within teams
  • Design processes to automate application analytics
  • Manage alerts, Blameless retrospectives and a just culture

Lab: Monitoring application performance with Application Insights

Lab: Integration between Azure DevOps and Microsoft Teams

Lab: Sharing Team Knowledge using Azure Project Wikis

After completing this module, students will be able to:

  • Implement tools to track feedback
  • Plan for continuous monitoring
  • Implement Application Insights
  • Use Kusto Query Language (KQL)
  • Implement routing for mobile applications
  • Configure App Center Diagnostics
  • Configure alerts
  • Create a bug tracker
  • Configure Azure Dashboards
  • Work with View Designer in Azure Monitor

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Who should attend this Microsoft training course?

Students in this course are interested in designing and implementing DevOps processes or in passing the Microsoft Azure DevOps Solutions certification exam.

  • Job role: DevOps Engineer
  • Preparation for exam: AZ-400

Prerequisites

Successful learners will have prior knowledge and understanding of:

  • Cloud computing concepts, including an understanding of PaaS, SaaS, and IaaS implementations.
  • Both Azure administration and Azure development with proven expertise in at least one of these areas.
  • Version control, Agile software development, and core software development principles. It would be helpful to have experience in an organization that delivers software.

Designing and Implementing Microsoft DevOps solutions AZ400 Course Overview

This course provides the knowledge and skills to design and implement DevOps processes and practices. Students will learn how to plan for DevOps, use source control, scale Git for an enterprise, consolidate artifacts, design a dependency management strategy, manage secrets, implement continuous integration, implement a container build strategy, design a release strategy, set up a release management workflow, implement a deployment pattern, and optimize feedback mechanisms.

What you will gain from taking this Microsoft training course:

  • Plan for the transformation with shared goals and timelines.
  • Select a project and identify project metrics and Key Performance Indicators (KPI's).
  • Create a team and agile organizational structure.
  • Design a tool integration strategy.
  • Design a license management strategy (e.g., Azure DevOps and GitHub users).
  • Design a strategy for end-to-end traceability from work items to working software.
  • Design an authentication and access strategy.
  • Design a strategy for integrating on-premises and cloud resources.
  • Describe the benefits of using Source Control.
  • Describe Azure Repos and GitHub.
  • Migrate from TFVC to Git.
  • Manage code quality, including technical debt SonarCloud, and other tooling solutions.
  • Build organizational knowledge on code quality.
  • Explain how to structure Git repos.
  • Describe Git branching workflows.
  • Leverage pull requests for collaboration and code reviews.
  • Leverage Git hooks for automation.
  • Use Git to foster inner source across the organization.
  • Explain the role of Azure Pipelines and its components.
  • Configure Agents for use in Azure Pipelines.
  • Explain why continuous integration matters.
  • Implement continuous integration using Azure Pipelines.
  • Design processes to measure end-user satisfaction and analyze user feedback.
  • Design processes to automate application analytics.
  • Manage alerts and reduce meaningless and non-actionable alerts.
  • Carry out blameless retrospectives and create a just culture.
  • Define an infrastructure and configuration strategy and appropriate toolset for a release pipeline and application infrastructure.
  • Implement compliance and security in your application infrastructure.
  • Describe the potential challenges with integrating open-source software.
  • Inspect open-source software packages for security and license compliance.
  • Manage organizational security and compliance policies.
  • Integrate license and vulnerability scans into build and deployment pipelines.
  • Configure build pipelines to access package security and license ratings.

Show moredown

What's included in this Microsoft training course?

  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

Show moredown

accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (4 days)

Online Self-paced (32 hours)

Microsoft Azure Security Technologies AZ500 Course Outline

Within this Microsoft training course, you will learn the following modules:

Module 1: Manage Identity and Access

This module covers Azure Active Directory, Azure Identity Protection, Enterprise Governance, Azure AD PIM, and Hybrid Identity.

Lessons

  • Azure Active Directory
  • Hybrid Identity
  • Azure Identity Protection
  • Azure AD Privileged Identity Management
  • Enterprise Governance

Lab: Role-Based Access Control

Lab: Azure Policy

Lab: Resource Manager Locks

Lab: MFA, Conditional Access and AAD Identity Protection

Lab: Azure AD Privileged Identity Management

Lab: Implement Directory Synchronization

After completing this module, students will be able to:

  • Implement enterprise governance strategies including role-based access control, Azure policies, and resource locks.
  • Implement an Azure AD infrastructure including users, groups, and multi-factor authentication.
  • Implement Azure AD Identity Protection including risk policies, conditional access, and access reviews.
  • Implement Azure AD Privileged Identity Management including Azure AD roles and Azure resources.
  • Implement Azure AD Connect including authentication methods and on-premises directory synchronization.

Module 2: Implement Platform Protection

This module covers perimeter, network, host, and container security.

Lessons

  • Perimeter Security
  • Network Security
  • Host Security
  • Container Security

Lab: Configuring and Securing ACR and AKS

Lab: Azure Firewall

Lab: Network Security Groups and Application Security Groups

After completing this module, students will be able to:

  • Implement perimeter security strategies including Azure Firewall.
  • Implement network security strategies including Network Security Groups and Application Security Groups.
  • Implement host security strategies including endpoint protection, remote access management, update management, and disk encryption.
  • Implement container security strategies including Azure Container Instances, Azure Container Registry, and Azure Kubernetes.

Module 3: Secure Data and Applications

This module covers Azure Key Vault, application security, storage security, and SQL database security.

Lessons

  • Azure Key Vault
  • Application Security
  • Storage Security
  • SQL Database Security

Lab: Key Vault (Implementing Secure Data by setting up Always Encrypted)

Lab: Securing Azure SQL Database

Lab: Service Endpoints and Securing Storage

After completing this module, students will be able to:

  • Implement Azure Key Vault including certificates, keys, and secretes.
  • Implement application security strategies including app registration, managed identities, and service endpoints.
  • Implement storage security strategies including shared access signatures, blob retention policies, and Azure Files authentication.
  • Implement database security strategies including authentication, data classification, dynamic data masking, and always encrypted.

Module 4: Manage Security Operations

This module covers Azure Monitor, Azure Security Center, and Azure Sentinel.

Lessons

  • Azure Monitor
  • Azure Security Center
  • Azure Sentinel

Lab: Azure Sentinel

Lab: Azure Security Center

Lab: Azure Monitor

After completing this module, students will be able to:

  • Implement Azure Monitor including connected sources, log analytics, and alerts.
  • Implement Azure Security Center including policies, recommendations, and just in time virtual machine access.
  • Implement Azure Sentinel including workbooks, incidents, and playbooks.

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Who should attend this Microsoft training course?

This course is for Azure Security Engineers who are planning to take the associated certification exam, or who are performing security tasks in their day-to-day job. This course would also be helpful to an engineer that wants to specialize in providing security for Azure-based digital platforms and play an integral role in protecting an organization's data.

  • Job role: Security Engineer.
  • Preparation for exam: AZ-500.

Prerequisites

Successful learners will have prior knowledge and understanding of:

  • Security best practices and industry security requirements such as defense in depth, least privileged access, role-based access control, multi-factor authentication, shared responsibility, and zero trust model.
  • Be familiar with security protocols such as Virtual Private Networks (VPN), Internet Security Protocol (IPSec), Secure Socket Layer (SSL), disk and data encryption methods.
  • Have some experience deploying Azure workloads. This course does not cover the basics of Azure administration, instead the course content builds on that knowledge by adding security specific information.
  • Have experience with Windows and Linux operating systems and scripting languages. Course labs may use PowerShell and the CLI.

Microsoft Azure Security Technologies AZ500 Course Overview

This course provides IT Security Professionals with the knowledge and skills needed to implement security controls, maintain an organization’s security posture, and identify and remediate security vulnerabilities. This course includes security for identity and access, platform protection, data and applications, and security operations.

What will you gain from this Microsoft training course?

  • Implement enterprise governance strategies including role-based access control, Azure policies, and resource locks.
  • Implement an Azure AD infrastructure including users, groups, and multi-factor authentication.
  • Implement Azure AD Identity Protection including risk policies, conditional access, and access reviews.
  • Implement Azure AD Privileged Identity Management including Azure AD roles and Azure resources.
  • Implement Azure AD Connect including authentication methods and on-premises directory synchronization.
  • Implement perimeter security strategies including Azure Firewall.
  • Implement network security strategies including Network Security Groups and Application Security Groups.
  • Implement host security strategies including endpoint protection, remote access management, update management, and disk encryption.
  • Implement container security strategies including Azure Container Instances, Azure Container Registry, and Azure Kubernetes.
  • Implement Azure Key Vault including certificates, keys, and secretes.
  • Implement application security strategies including app registration, managed identities, and service endpoints.
  • Implement storage security strategies including shared access signatures, blob retention policies, and Azure Files authentication.
  • Implement database security strategies including authentication, data classification, dynamic data masking, and always encrypted.
  • Implement Azure Monitor including connected sources, log analytics, and alerts.
  • Implement Azure Security Center including policies, recommendations, and just in time virtual machine access.
  • Implement Azure Sentinel including workbooks, incidents, and playbooks.

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What's included in this Microsoft training course?

  • Experienced tutor
  • Labs

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accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (3 days)

Online Self-paced (24 hours)

Designing and Implementing a Data Science Solution on Azure DP100 Course Outline

Within this training course you will learn the following modules:

Module 1: Getting Started with Azure Machine Learning

In this module, you will learn how to provision an Azure Machine Learning workspace and use it to manage machine learning assets such as data, compute, model training code, logged metrics, and trained models. You will learn how to use the web-based Azure Machine Learning studio interface as well as the Azure Machine Learning SDK and developer tools like Visual Studio Code and Jupyter Notebooks to work with the assets in your workspace.

Lessons

  • Introduction to Azure Machine Learning
  • Working with Azure Machine Learning

Lab: Create an Azure Machine Learning Workspace

After completing this module, you will be able to

  • Provision an Azure Machine Learning workspace
  • Use tools and code to work with Azure Machine Learning

Module 2: Visual Tools for Machine Learning

This module introduces the Automated Machine Learning and Designer visual tools, which you can use to train, evaluate, and deploy machine learning models without writing any code.

Lessons

  • Automated Machine Learning
  • Azure Machine Learning Designer

Lab: Use Automated Machine Learning

Lab: Use Azure Machine Learning Designer

After completing this module, you will be able to

  • Use automated machine learning to train a machine learning model
  • Use Azure Machine Learning designer to train a model

Module 3: Running Experiments and Training Models

In this module, you will get started with experiments that encapsulate data processing, model training code, and use them to train machine learning models.

Lessons

  • Introduction to Experiments
  • Training and Registering Models

Lab: Train Models

Lab: Run Experiments

After completing this module, you will be able to

  • Run code-based experiments in an Azure Machine Learning workspace
  • Train and register machine learning models

Module 4: Working with Data

Data is a fundamental element in any machine learning workload, so in this module, you will learn how to create and manage datastores and datasets in an Azure Machine Learning workspace, and how to use them in model training experiments.

Lessons

  • Working with Datastores
  • Working with Datasets

Lab: Work with Data

After completing this module, you will be able to

  • Create and use datastores
  • Create and use datasets

Module 5: Working with Compute

One of the key benefits of the cloud is the ability to leverage compute resources on demand and use them to scale machine learning processes to an extent that would be infeasible on your own hardware. In this module, you'll learn how to manage experiment environments that ensure consistent runtime consistency for experiments, and how to create and use compute targets for experiment runs.

Lessons

  • Working with Environments
  • Working with Compute Targets

Lab: Work with Compute

After completing this module, you will be able to

  • Create and use environments
  • Create and use compute targets

Module 6: Orchestrating Operations with Pipelines

Now that you understand the basics of running workloads as experiments that leverage data assets and compute resources, it's time to learn how to orchestrate these workloads as pipelines of connected steps. Pipelines are key to implementing an effective Machine Learning Operationalization (ML Ops) solution in Azure, so you'll explore how to define and run them in this module.

Lessons

  • Introduction to Pipelines
  • Publishing and Running Pipelines

Lab: Create a Pipeline

After completing this module, you will be able to:

  • Create pipelines to automate machine learning workflows
  • Publish and run pipeline services

Module 7: Deploying and Consuming Models

Models are designed to help decision making through predictions, so they're only useful when deployed and available for an application to consume. In this module learn how to deploy models for real-time inferencing, and for batch inferencing.

Lessons

  • Real-time Inferencing
  • Batch Inferencing
  • Continuous Integration and Delivery

Lab: Create a Real-time Inferencing Service

Lab: Create a Batch Inferencing Service

After completing this module, you will be able to

  • Publish a model as a real-time inference service
  • Publish a model as a batch inference service
  • Describe techniques to implement continuous integration and delivery

Module 8: Training Optimal Models

By this stage of the course, you've learned the end-to-end process for training, deploying, and consuming machine learning models; but how do you ensure your model produces the best predictive outputs for your data? In this module, you'll explore how you can use hyperparameter tuning and automated machine learning to take advantage of cloud-scale compute and find the best model for your data.

Lessons

  • Hyperparameter Tuning
  • Automated Machine Learning

Lab: Use Automated Machine Learning from the SDK

Lab: Tune Hyperparameters

After completing this module, you will be able to

  • Optimize hyperparameters for model training
  • Use automated machine learning to find the optimal model for your data

Module 9: Responsible Machine Learning

Data scientists have a duty to ensure they analyze data and train machine learning models responsibly, respecting individual privacy, mitigating bias, and ensuring transparency. This module explores some considerations and techniques for applying responsible machine learning principles.

Lessons

  • Differential Privacy
  • Model Interpretability
  • Fairness

Lab: Explore Differential provacy

Lab: Interpret Models

Lab: Detect and Mitigate Unfairness

After completing this module, you will be able to

  • Apply differential provacy to data analysis
  • Use explainers to interpret machine learning models
  • Evaluate models for fairness

Module 10: Monitoring Models

After a model has been deployed, it's important to understand how the model is being used in production, and to detect any degradation in its effectiveness due to data drift. This module describes techniques for monitoring models and their data.

Lessons

  • Monitoring Models with Application Insights
  • Monitoring Data Drift

Lab: Monitor Data Drift

Lab: Monitor a Model with Application Insights

After completing this module, you will be able to

  • Use Application Insights to monitor a published model
  • Monitor data drift

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Who should attend this course?

This course is aimed at data scientists and those with significant responsibilities in training and deploying machine learning models.

Job role: Data Scientist

Preparation for exam: DP-100

Prerequisites

Before attending, you should understand the fundamentals of Azure as well as understand the following:

  • Data science including how to prepare data, train models, and evaluate competing models to select the best one.
  • How to program in the Python programming language and use the Python libraries: pandas, scikit-learn, matplotlib, and seaborn

Designing and Implementing a Data Science Solution on Azure DP100 Course Overview

Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure.

 

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Designing and Implementing a Data Science Solution on Azure (M-DP100)

The Microsoft Azure Data Scientist Associate certification exam covers the following areas:

  • Define and prepare the development environment (15-20%)
  • Prepare data for modeling (25-30%)
  • Perform feature engineering (15-20%)
  • Develop models (40-45%)

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accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (4 days)

Online Self-paced (32 hours)

Designing and implementing a Microsoft Azure AI Solution AI102 Course Outline

Within this Microsoft training you will learn the following modules:

Module 1: Introduction to AI on Azure

Artificial Intelligence (AI) is increasingly at the core of modern apps and services. In this module, you'll learn about some common AI capabilities that you can leverage in your apps, and how those capabilities are implemented in Microsoft Azure. You'll also learn about some considerations for designing and implementing AI solutions responsibly.

Lessons

  • Introduction to Artificial Intelligence
  • Artificial Intelligence in Azure

After completing this module, students will be able to:

  • Describe considerations for creating AI-enabled applications
  • Identify Azure services for AI application development

Module 2: Developing AI Apps with Cognitive Services

Cognitive Services are the core building blocks for integrating AI capabilities into your apps. In this module, you'll learn how to provision, secure, monitor, and deploy cognitive services.

Lessons

  • Getting Started with Cognitive Services
  • Using Cognitive Services for Enterprise Applications

Lab: Get Started with Cognitive Services
Lab: Manage Cognitive Services Security
Lab: Monitor Cognitive Services
Lab: Use a Cognitive Services Container

After completing this module, students will be able to:

  • Provision and consume cognitive services in Azure
  • Manage cognitive services security
  • Monitor cognitive services
  • Use a cognitive services container

Module 3: Getting Started with Natural Language Processing

Natural Language processing (NLP) is a branch of artificial intelligence that deals with extracting insights from written or spoken language. In this module, you'll learn how to use cognitive services to analyze and translate text.

Lessons

  • Analyzing Text
  • Translating Text

Lab: Translate Text

Lab: Analyze Text

After completing this module, students will be able to:

  • Use the Text Analytics cognitive service to analyze text
  • Use the Translator cognitive service to translate text

Module 4: Building Speech-Enabled Applications

Many modern apps and services accept spoken input and can respond by synthesizing text. In this module, you'll continue your exploration of natural language processing capabilities by learning how to build speech-enabled applications.

Lessons

  • Speech Recognition and Synthesis
  • Speech Translation

Lab: Recognize and Synthesize Speech
Lab: Translate Speech

After completing this module, students will be able to:

  • Use the Speech cognitive service to recognize and synthesize speech
  • Use the Speech cognitive service to translate speech

Module 5: Creating Language Understanding Solutions

To build an application that can intelligently understand and respond to natural language input, you must define and train a model for language understanding. In this module, you'll learn how to use the Language Understanding service to create an app that can identify user intent from natural language input.

Lessons

  • Creating a Language Understanding App
  • Publishing and Using a Language Understanding App
  • Using Language Understanding with Speech

Lab: Create a Language Understanding Client Application
Lab: Create a Language Understanding App
Lab: Use the Speech and Language Understanding Services

After completing this module, students will be able to:

  • Create a Language Understanding app
  • Create a client application for Language Understanding
  • Integrate Language Understanding and Speech

Module 6: Building a QnA Solution

One of the most common kinds of interaction between users and AI software agents is for users to submit questions in natural language, and for the AI agent to respond intelligently with an appropriate answer. In this module, you'll explore how the QnA Maker service enables the development of this kind of solution.

Lessons

  • Creating a QnA Knowledge Base
  • Publishing and Using a QnA Knowledge Base

Lab: Create a QnA Solution

After completing this module, students will be able to:

  • Use QnA Maker to create a knowledge base
  • Use a QnA knowledge base in an app or bot

Module 7: Conversational AI and the Azure Bot Service

Bots are the basis for an increasingly common kind of AI application in which users engage in conversations with AI agents, often as they would with a human agent. In this module, you'll explore the Microsoft Bot Framework and the Azure Bot Service, which together provide a platform for creating and delivering conversational experiences.

Lessons

  • Bot Basics
  • Implementing a Conversational Bot

Lab: Create a Bot with the Bot Framework SDK
Lab: Create a Bot with Bot Framework Composer

After completing this module, students will be able to:

  • Use the Bot Framework SDK to create a bot
  • Use the Bot Framework Composer to create a bot

Module 8: Getting Started with Computer Vision

Computer vision is an area of artificial intelligence in which software applications interpret visual input from images or video. In this module, you'll start your exploration of computer vision by learning how to use cognitive services to analyze images and video.

Lessons

  • Analyzing Images
  • Analyzing Videos

Lab: Analyze Video
Lab: Analyze Images with Computer Vision

After completing this module, students will be able to:

  • Use the Computer Vision service to analyze images
  • Use Video Analyzer to analyze videos

Module 9: Developing Custom Vision Solutions

While there are many scenarios where pre-defined general computer vision capabilities can be useful, sometimes you need to train a custom model with your own visual data. In this module, you'll explore the Custom Vision service, and how to use it to create custom image classification and object detection models.

Lessons

  • Image Classification
  • Object Detection

Lab: Classify Images with Custom Vision
Lab: Detect Objects in Images with Custom Vision

After completing this module, students will be able to:

  • Use the Custom Vision service to implement image classification
  • Use the Custom Vision service to implement object detection

Module 10: Detecting, Analyzing, and Recognizing Faces

Facial detection, analysis, and recognition are common computer vision scenarios. In this module, you'll explore the user of cognitive services to identify human faces.

Lessons

  • Detecting Faces with the Computer Vision Service
  • Using the Face Service

Lab: Detect, Analyze, and Recognize Faces

After completing this module, students will be able to:

  • Detect faces with the Computer Vision service
  • Detect, analyze, and recognize faces with the Face service

Module 11: Reading Text in Images and Documents

Optical character recognition (OCR) is another common computer vision scenario, in which software extracts text from images or documents. In this module, you'll explore cognitive services that can be used to detect and read text in images, documents, and forms.

Lessons

  • Reading text with the Computer Vision Service
  • Extracting Information from Forms with the Form Recognizer service

Lab: Read Text in Images
Lab: Extract Data from Forms

After completing this module, students will be able to:

  • Use the Computer Vision service to read text in images and documents
  • Use the Form Recognizer service to extract data from digital forms

Module 12: Creating a Knowledge Mining Solution

Many AI scenarios involve intelligently searching for information based on user queries. AI-powered knowledge mining is an increasingly important way to build intelligent search solutions that use AI to extract insights from large repositories of digital data and enable users to find and analyze those insights.

Lessons

  • Implementing an Intelligent Search Solution
  • Developing Custom Skills for an Enrichment Pipeline
  • Creating a Knowledge Store

Lab: Create a Custom Skill for Azure Cognitive Search
Lab: Create an Azure Cognitive Search solution
Lab: Create a Knowledge Store with Azure Cognitive Search

After completing this module, students will be able to:

  • Create an intelligent search solution with Azure Cognitive Search
  • Implement a custom skill in an Azure Cognitive Search enrichment pipeline
  • Use Azure Cognitive Search to create a knowledge store

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Who should attend this Microsoft training course?

Software engineers concerned with building, managing, and deploying AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and conversational AI solutions on Azure.

  • Job role: AI Engineer.
  • Preparation for exam: AI-102.

Microsoft Training Prerequisites

Before attending this course, students must have:

  • Knowledge of Microsoft Azure and ability to navigate the Azure portal
  • Knowledge of either C# or Python
  • Familiarity with JSON and REST programming semantics

Designing and implementing a Microsoft Azure AI Solution AI102 Course Overview

AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. The course will use C# or Python as the programming language.

What you gain from this training course?

  • Describe considerations for AI-enabled application development
  • Create, configure, deploy, and secure Azure Cognitive Services
  • Develop applications that analyze text
  • Develop speech-enabled applications
  • Create applications with natural language understanding capabilities
  • Create QnA applications
  • Create conversational solutions with bots
  • Use computer vision services to analyze images and videos
  • Create custom computer vision models
  • Develop applications that detect, analyze, and recognize faces
  • Develop applications that read and process text in images and documents
  • Create intelligent search solutions for knowledge mining

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What's included in this Artificial Intelligence Course?

  • Experienced Instructor
  • Labs

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accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (2 days)

Online Self-paced (16 hours)

Migrate SQL Workloads to Azure DP050​ Course Outline

Module 1: Introducing Data Platform Modernisation

  • Understand Data Platform Modernisation
  • Understanding the Stages of Migration
  • Data Migration Paths

Lab: Introducing Data Platform Modernisation

  • Understand Data Platform Modernisation
  • Understand the Stages of Migration
  • Data Migration Paths

Module 2: Choose the Right Tools for Data Migration

  • Discover the Database Migration Guide
  • Build Your Data Estate Inventory Using Map Toolkit
  • Identify Migration Candidates Using Data Migration Assistant
  • Evaluate a Data Workload Using Database Experimentation Assistant
  • Data Migration using Azure Database Migration Service
  • Migrate Non-SQL Server Workloads to Azure Using SQL Migration Assistant

Lab: Choose the Right Tools for Data Migration

  • Identify Migration Candidates using Data Migration Assistant
  • Evaluate a Data Workload using Database Experimentation Assistant

Module 3: Migrating SQL Workloads to Azure Virtual Machines

  • Considerations of SQL Server to Azure VM Migrations
  • SQL Workloads to Azure VM Migration Options
  • Implementing High Availability and Disaster Recovery Scenarios

Lab: Migrating SQL Workloads to Azure Virtual Machines

Module 4: Migrate SQL Workloads to Azure SQL Databases

  • Choose the Right SQL Server Instance Option in Azure
  • Migrate SQL Server to Azure SQL DB Offline
  • Migrate SQL Server to Azure SQL DB Online
  • Load and Move Data to Azure SQL Database

Lab: Migrate SQL Workloads to Azure SQL Databases

Module 5: Migrate SQL Workloads to Azure SQL Database Managed Instance

  • Evaluate Migration Scenarios to SQL Database Managed Instance
  • Migrate to SQL Database Managed Instance
  • Load and Move Data to SQL Database Managed Instance
  • Application Configuration and Optimisation

Lab: Migrate SQL Workloads to Azure SQL Database Managed Instance

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Prerequisites

To attend Migrate SQL Workloads to Azure DP050 training course, delegates should have prior knowledge of cloud computing concepts and professional experience in implementing SQL solutions. It will be advantageous if they have:

  • Experience working with and maintaining SQL workloads
  • Experience working with Azure, like deploying and managing resources

Audience

This Migrate SQL Workloads to Azure DP050 training course is ideal for anyone who wants to gain knowledge of migrating data platform technologies. However, this will be more beneficial for:

  • Data Professionals
  • Data Architects
  • Data Engineers

Migrate SQL Workloads to Azure DP050​ Course Overview

Microsoft SQL Server, like any other application, uses the workloads to manage client requests efficiently. Azure SQL helps in managing resource consumption and server workloads. Studying Migrate SQL Workloads to Azure training DP050T00 course will help learners to explore each stage of the data platform modernisation process. It provides individuals with seamless hybrid features, intelligent security, and cost-saving on Azure. It helps organisations by fulfilling the needs of SQL Server migration and Windows server migrations. Having this training will surely help individuals to undertake a variety of tremendous job opportunities in various companies.

This 2-day Migrate SQL Workloads to Azure DP050 training course covers all the essential topics by which delegates will become fully familiar with data platform modernisation. During this training, delegates will learn how to migrate non-SQL server workloads to Azure using SQL migration assistant. They will also learn how to choose the right SQL server instance option in Azure, SQL workloads to Azure VM migration options, migrate to SQL database managed instance, migrate SQL server to Azure SQL DB offline, and many more. Our highly professional trainer with years of experience in teaching Microsoft courses will conduct this training and will help you get a complete understanding of this course.   

This training will cover various essential topics, such as: 

  • Data migration paths
  • Migrate SQL Server to Azure SQL DB online
  • Application configuration and optimisation
  • Build data estate inventory using map toolkit
  • Data migration using Azure database migration service

After attending this Migrate SQL Workloads to Azure training course, delegates will be able to identify migration candidates using data migration assistants. They will also be able to implement high availability and disaster recovery scenarios.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

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accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Migrate NoSQL Workloads to Azure Cosmos DB (MDP060)​ Course Outline

Module 1: Building Globally Distributed Applications with Cosmos DB
Lessons

  • Cosmos DB Overview
  • Cosmos DB APIs
  • Provisioning Throughput
  • Partitioning/Sharding Best Practices

Lab: Practice Labs

  • Create Cosmos DB Account
  • Configure RUs

Module 2: Migrate MongoDB Workloads to Cosmos DB
Lessons

  • Understand Migration Benefits
  • Migration Planning
  • Data Migration
  • Application Migration
  • Post-Migration considerations

Lab: Practice Labs

  • Create a Migration Project
  • Define Source and Target
  • Perform Migration
  • Verify Migration

Module 3: Migrate Cassandra DB Workloads to Cosmos DB

Lessons

  • Understand Migration Benefits
  • Migration Planning
  • Data Migration
  • Application Migration
  • Post-Migration Considerations

Lab: Practice Labs

  • Export the Schema
  • Move Data Using CQLSH COPY
  • Move Data Using Spark
  • Verify Migration

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Prerequisites

There are no prerequisites for this course.

Audience

This course is for IT Professionals who want to learn about Microsoft Technologies.

Migrate NoSQL Workloads to Azure Cosmos DB (MDP060)​ Course Overview

In this course, delegates will learn about Cosmos DB and how to migrate MongoDB and Cassandra workloads to Cosmos DB. Delegates will learn how to build Globally Distributed Applications with Cosmos DB. In this 1-day course, delegates will also learn how to migrate MongoDB Workloads to Cosmos DB and how to migrate Cassandra DB Workloads to Cosmos DB.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor
  • Refreshments

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accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Migrate Open Source Data Workloads to Azure (DP070)​ Course Outline

Module 1 - Migrate to Azure SQL DB for MySQL and PostgreSQL

This module will explain about benefits and architecture of Azure SQL DB.

Lessons

  • OSS Databases Overview
  • Common OSS Database Workloads
  • Customer Challenges in Migration

Lab: Creating Source OSS Databases

  • Installation of Postgres Migration DB Server
  • Installation of MySQL Migration DB Server
  • Backups/Data Dumps from Postgres/MySQL
  • Restore from Data Dumps

Module 2 - Migrate On-Premises MySQL to Azure SQL DB for MySQL

In this module, delegates will learn about the benefits and process of migrating MySQL workloads to Azure SQL DB.

Lessons

  • Configure and Manage Azure SQL DB for MySQL
  • Migrate On-Premises MySQL to SQL DB for MySQL
  • Application Migration
  • Post-Migration Considerations

Lab: Migrating MySQL DB Workloads to Azure SQL DB

  • Migrating MySQL DB Workloads to Azure SQL DB
  • Define Source and Target DBs 
  • Perform Migration
  • Verify Migration

Module 3 - Migrate On-Premises PostgreSQL to Azure SQL DB for PostgreSQL

In this module, delegates will get an understanding of the benefits and process of migrating PostgreSQL DB workloads to Azure SQL DB

Lessons

  • Configure and Manage Azure SQL DB for PostgreSQL
  • Migrate On-Premises MySQL to SQL DB for PostgreSQL
  • Application Migration
  • Post-Migration Considerations

Lab: Migrating PostgreSQL DB Workloads to Azure SQL DB

  • Configure Azure SQL DB for PostgreSQL
  • Define Source and Target DBs
  • Perform Migration
  • Verify Migration

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Prerequisites

There are no formal prerequisites for this course.

Audience

This course is designed for IT Professionals.

Migrate Open Source Data Workloads to Azure (DP070)​ Course Overview

Technically, the database is an organised collection of data. Data workloads contain the data, database engine to access the data, and the database schema for logical structure. For the world’s innovation, AI technology, Machine learning, and cloud services, Microsoft Azure is a leading contender to execute or drive database migration to the cloud. For database administrator, this is the perfect opportunity to migrate data workloads to the cloud platform. Azure is the best cloud platform for simplifying the administration activities, high scalability and availability. From a security perspective, Azure is PCI compliance. It provides advanced-level security for essential and sensitive database. Within an organisation, Azure also helps to improved business agility.

This 1-day course is designed to get a better understanding of how data workloads set up on the Azure Cloud platform. In this course, delegates will learn about SQL Database and gain knowledge of how to migrate MySQL and PostgreSQL workloads to Azure SQL Database.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor
  • Refreshments

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accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (1 days)

Online Self-paced (8 hours)

Implementing a Machine Learning Solution with Microsoft Azure Databricks DP090 Course Outline

Within this training course you will learn the following modules:

Module 1: Introduction to Azure Databricks

In this module, you will learn how to provision an Azure Databricks workspace and cluster and use them to work with data.

Lessons

  • Getting Started with Azure Databricks
  • Working with Data in Azure Databricks

Lab: Getting Started with Azure Databricks

Lab: Working with Data in Azure Databricks

After completing this module, you will be able to:

  • Provision an Azure Databricks workspace and cluster
  • Use Azure Databricks to work with data

Module 2: Training and Evaluating Machine Learning Models

In this module, you will learn how to use Azure Databricks to prepare data for modeling, and train and validate a machine learning model.

Lessons

  • Preparing Data for Machine Learning
  • Training a Machine Learning Model

Lab: Training a Machine Learning Model

Lab: Preparing Data for Machine Learning

After completing this module, you will be able to use Azure Databricks to:

  • Prepare data for modeling
  • Train and validate a machine learning model

Module 3: Managing Experiments and Models

In this module, you will learn how to use MLflow to track experiments running in Azure Databricks, and how to manage machine learning models.

Lessons

  • Using MLflow to Track Experiments
  • Managing Models

Lab: Using MLflow to Track Experiments

Lab: Managing Models

After completing this module, you will be able to:

  • Use MLflow to track experiments
  • Manage models

Module 4: Integrating Azure Databricks and Azure Machine Learning

In this module, you will learn how to integrate Azure Databricks with Azure Machine Learning

Lessons

  • Tracking Experiments with Azure Machine Learning
  • Deploying Models

Lab: Deploying Models in Azure Machine Learning

Lab: Running Experiments in Azure Machine Learning

After completing this module, you will be able to:

  • Run Azure Machine Learning experiments on Azure Databricks compute
  • Deploy models trained on Azure Databricks to Azure Machine Learning

Show moredown

Who should attend this Microsoft training course?

This course is designed for data scientists with experience of Pythion who need to learn how to apply their data science and machine learning skills on Azure Databricks

Job role: Data Scientist

Prerequisites

Before attending this course, you should have experience of using Python to work with data, and some knowledge of machine learning concepts.

Implementing a Machine Learning Solution with Microsoft Azure Databricks DP090 Course Overview

Azure Databricks is a cloud-scale platform for data analytics and machine learning. In this one-day course, you'll learn how to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning.

What you will gain from taking this training course:

  • Provision an Azure Databricks workspace and cluster
  • Use Azure Databricks to train a machine learning model
  • Use MLflow to track experiments and manage machine learning models
  • Integrate Azure Databricks with Azure Machine Learning

Show moredown

​What's included in this Microsoft training course?

  • Experienced Instructor
  • Labs

Show moredown

accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (4 days)

Online Self-paced (32 hours)

Configuring and Operating a Hybrid Cloud with Microsoft Azure Stack Course Outline | Azure Training |

This course includes the following modules:

Module 1: Overview of Azure Stack Hub

In this module, you will learn how Azure Stack Hub is an extension of Azure that provides a way to run apps in an on-premises environment and deliver Azure services in your datacenter.

Lessons

  • Azure Stack Hub
  • Datacenter integration
  • Azure Stack Hub PowerShell
  • Module review questions

After completing this module, students will be able to:

  • Describe edge and disconnected solutions
  • Describe Azure Stack Hub integrated systems architecture
  • Explain Azure Stack Hub deployment options
  • Define differences between Azure Stack Hub, Azure Stack HCI, and global Azure

Module 2: Provide Services

In this module, you will learn how to populate Azure Stack Hub Marketplace in a disconnected environment, deploy an App Services resource provider, deploy Event Hubs resource provides, create and manage quotas, plans, offers, and subscriptions, and manage usage and billing.

Lessons

  • Manage Azure Stack Hub Marketplace
  • Offer an App Services resource provider
  • Offer an Event Hubs resource provider
  • Offer services
  • Manage usage and billing
  • Module review questions
    • Lab : Manage offers and plans in Azure Stack Hub
    • Lab : Add custom Marketplace Items by using the Azure Gallery Packager
    • Lab : Validate Azure Resource Manager (ARM) Templates with Azure Stack Hub
    • Lab : Optional Lab : Implement SQL Server Resource Provider in Azure Stack Hub

After completing this module, students will be able to:

  • Create a custom Azure Stack Hub Marketplace item
  • Deploy and update an App Services resource provider
  • Plan an Event Hubs resource provider deployment
  • Create and manage user subscriptions
  • Manage usage and billing in multi-tenant and CSP scenarios

Module 3: Implement Data Center Integration

In this module, you will learn how prepare an Stack Hub deployment, recommend and validate certificates, and register in a connected and disconnected environment.

Lessons

  • Prepare for Azure Stack Hub deployment
  • Manage Azure Stack Hub registration
  • Module review questions

After completing this module, students will be able to:

  • View and retrieve usage data by using the Usage API
  • Recommend a name resolution strategy
  • Validate identity provider integration
  • Validate certificates
  • Recommend a registration mode

Module 4: Manage Identity and Access for Azure Stack Hub

In this module, you will learn how to configure the Azure Stack Hub home directory, register the guest tenant directory with Azure Stack Hub, and identify an appropriate method for access (service principal, users, groups).

Lessons

  • Manage multi-tenancy
  • Manage access
  • Module review questions
    • Lab : Delegate Offer Management in Azure Stack Hub
    • Lab : Manage Service Principals in Azure Stack Hub

After completing this module, students will be able to:

  • Register the guest tenant directory with Azure Stack Hub
  • Update the guest tenant directory
  • Configure access in Azure Stack Hub
  • Create a custom role

Module 5: Manage the Azure Stack Hub Infrastructure

In this module, you will learn how monitor system health by using the REST API, monitor system health by using Syslog Server, collect diagnostic logs on demand by using Powershell, configure a storage target for infrastructure backup, and download and import update packages manually.

Lessons

  • Manage system health
  • Azure Monitor on Azure Stack Hub
  • Plan and configure business continuity and disaster recovery
  • Manage capacity
  • Update infrastructure
  • Manage Azure Stack Hub by using privileged endpoints
  • Module review questions
    • Lab : Connect to Azure Stack Hub via PowerShell
    • Lab : Access the Privileged Endpoint in Azure Stack Hub
    • Lab : Manage Log Collection in Azure Stack Hub
    • Lab : Configure and manage Azure Stack Hub Storage Accounts
    • Lab : Manage Public IP Addresses in Azure Stack Hub
    • Lab : Configure Azure Stack Hub Infrastructure Backup

After completing this module, students will be able to:

  • Include resource providers such as Event Hubs
  • Manage field replacement or repair
  • Configure storage targets for infrastructure backups
  • Update Azure Stack Hub
  • Unlock a support session
  • Connect to a privileged endpoin
  • Perform system diagnostics by using Test-AzureStack

Show moredown

Who Should Attend this Azure Course?

The primary audience for this course is service administrators and DevOps or cloud architects who are interested in using Microsoft Azure Stack to provide cloud services to their end-users or customers from within their own datacentre.

Prerequisites

Before attending this course, delegates should possess or be able to demonstrate:

  • Working knowledge of Windows Server 2016
  • Working knowledge of SQL Server 2014
  • Working knowledge of Microsoft Azure

Configuring and Operating a Hybrid Cloud with Microsoft Azure Stack Course Overview | Azure Training

This 5-day course is intended to provide delegates with the key knowledge required to deploy and configure Microsoft Azure Stack. During the course, they will learn the features and functionalities of Microsoft Azure Stack, how to deploy and manage Microsoft Azure Stack, how to configure resources and monitor Microsoft Azure Stack, and more.

This Configuring and Operating a Hybrid Cloud with Microsoft Azure Stack course is fully accredited by Microsoft through the Microsoft Silver Partnership held by The Knowledge Academy.

After completing this course, delegates will be able to:

  • Describe the components and architecture of Microsoft Azure Stack
  • Deploy Microsoft Azure Stack
  • Understand the Windows Server 2016 features used in Microsoft Azure Stack
  • Understand how DevOps use Microsoft Azure Stack
  • Offer resources in Microsoft Azure Stack
  • Manage IaaS in Microsoft Azure Stack
  • Manage PaaS in Microsoft Azure Stack
  • Manage updates in Microsoft Azure Stack
  • Perform monitoring and troubleshooting in Microsoft Azure Stack
  • Understand how licensing and billing works in Microsoft Azure Stack

Show moredown

What's included in this Azure Training Course?

The Knowledge Academy does not provide an examination for this course. Delegates will be given access to:

  • Tuition from one of our expert trainers
  • Certificate of completion
  • Refreshments

Show moredown

accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (4 days)

Online Self-paced (32 hours)

Designing and Implementing CloudNative Applications Using Microsoft Azure Cosmos DB DP420 Course Outline

Within this Microsoft training course, you will learn the following modules:

Module 1: Get started with Azure Cosmos DB SQL API

Modern apps thrive on real-time data from different sources and shaped in different forms. These apps require a modern database that can handle the variety and velocity of data that will be thrown at it. In this module, we will explore Azure Cosmos DB and how the SQL API can solve some of the problems presented by modern applications.

Lessons

  • Introduction to Azure Cosmos DB SQL API
  • Try Azure Cosmos DB SQL API

Lab: Exercise: Create an Azure Cosmos DB SQL API account

After completing this module, students will be able to:

  • Evaluate whether Azure Cosmos DB SQL API is the right database for your application
  • Describe how the features of the Azure Cosmos DB SQL API are appropriate for modern applications
  • Create a new Azure Cosmos DB SQL API account
  • Create database, container, and item resources for an Azure Cosmos DB SQL API account

Module 2: Plan and implement Azure Cosmos DB SQL API

Creating a new Azure Cosmos DB account often requires making a lot of configuration choices that can, at first, be daunting. While the defaults fit a lot of scenarios, it makes the most sense to familiarize yourself with the configuration options to ensure that your account and resources are optimally configured for your solution. In this module, you will learn how to prepare and configure an Azure Cosmos DB account and resources for a new solution.

Lessons

  • Plan Resource Requirements
  • Configure Azure Cosmos DB SQL API database and containers
  • Moving data into and out of Azure Cosmos DB SQL API

Lab: Exercise: Configure throughput for Azure Cosmos DB SQL API with the Azure portal

Lab: Exercise: Migrate existing data using Azure Data Factory

After completing this module, students will be able to:

  • Evaluate various requirements of your application
  • Plan for scale and retention requirements
  • Configure throughput allocation
  • Configure time-to-live values
  • Migrate data using Azure services
  • Migrate data using Spark or Kafka

Module 3: Connect to Azure Cosmos DB SQL API with the SDK

There are various SDKs available to connect to the Azure Cosmos DB SQL API from many popular programming languages including, but not limited to .NET (C#), Java, Python, and JavaScript (Node.js). In this module, you will get hands-on with with the .NET SDK for the Azure Cosmos DB SQL API.

Lessons

  • Use the Azure Cosmos DB SQL API SDK
  • Configure the Azure Cosmos DB SQL API SDK

Lab: Exercise: Configure the Azure Cosmos DB SQL API SDK for offline development

Lab: Exercise: Connect to Azure Cosmos DB SQL API with the SDK

After completing this module, students will be able to:

  • Integrate the Microsoft.Azure.Cosmos SDK library from NuGet
  • Connect to an Azure Cosmos DB SQL API account using the SDK and .NET
  • Configure the SDK for offline development
  • Troubleshoot common connection errors
  • Implement parallelism in the SDK
  • Configure logging using the SDK

Module 4: Access and manage data with the Azure Cosmos DB SQL API SDKs

The SQL API SDK for Azure Cosmos DB is used to perform various point operations, perform transactions, and to process bulk data. In this module, you will use the SDK to manipulate documents either individually or in groups.

Lessons

  • Implement Azure Cosmos DB SQL API point operations
  • Perform cross-document transactional operations with the Azure Cosmos DB SQL API
  • Process bulk data in Azure Cosmos DB SQL API

Lab: Exercise: Create and update documents with the Azure Cosmos DB SQL API SDK

Lab: Exercise: Batch multiple point operations together with the Azure Cosmos DB SQL API SDK

Lab: Exercise: Move multiple documents in bulk with the Azure Cosmos DB SQL API SDK

After completing this module, students will be able to:

  • Perform CRUD operations using the SDK
  • Configure TTL for a specific document
  • Implement optimistic concurrency control for an operation
  • Create a transactional batch and review results
  • Create a bulk operation
  • Review the results of a bulk operation
  • Implement bulk operation best practices

Module 5: Execute queries in Azure Cosmos DB SQL API

The Azure Cosmos DB SQL API supports Structured Query Language (SQL) as a JSON query language. In this module, you will learn how to create efficient queries using the SQL query language.

Lessons

  • Query the Azure Cosmos DB SQL API
  • Author complex queries with the Azure Cosmos DB SQL API

Lab: Exercise: Paginate cross-product query results with the Azure Cosmos DB SQL API SDK

Lab: Exercise: Execute a query with the Azure Cosmos DB SQL API SDK

After completing this module, students will be able to:

  • Create and execute a SQL query
  • Project query results
  • Use built-in functions in a query
  • Implement a corelated subquery
  • Create a cross-product query

Module 6: Define and implement an indexing strategy for Azure Cosmos DB SQL API

By default, Azure Cosmos DB automatically indexes all paths of documents stored using the SQL API. This is great for developing new applications as you can create complex queries almost immediately. As your application matures, you can customize your indexing policy to better match the needs of your solution. In this module, you will learn how to create a custom indexing policy.

Lessons

  • Define indexes in Azure Cosmos DB SQL API
  • Customize indexes in Azure Cosmos DB SQL API

Lab: Exercise: Review the default index policy for an Azure Cosmos DB SQL API container with the portal

Lab: Exercise: Configure an Azure Cosmos DB SQL API container's index policy with the portal

After completing this module, students will be able to:

  • View and understand the default indexing policy for a SQL API container
  • Customize the indexing policy for a container
  • Use a composite index in an indexing policy

Module 7: Integrate Azure Cosmos DB SQL API with Azure services

Azure Cosmos DB has tight integration available with many other Azure servicers such as Azure Functions, Azure Cognitive Search, Azure Event Hubs, Azure Storage, Azure Data Factory, and Azure Stream Analytics. Going even further, you can use the change feed to integrate Azure Cosmos DB with many other services both in and out of Azure. In this module, we will integrate Azure Cosmos DB with both Azure Functions and Azure Cognitive Search. We will also explore the change feed using the SDK.

Lessons

  • Consume an Azure Cosmos DB SQL API change feed using the SDK
  • Handle events with Azure Functions and Azure Cosmos DB SQL API change feed
  • Search Azure Cosmos DB SQL API data with Azure Cognitive Search

Lab: Exercise: Archive Azure Cosmos DB SQL API data using Azure Functions

Lab: Exercise: Process change feed events using the Azure Cosmos DB SQL API SDK

Lab: Exercise: Archive data using Azure Functions and Azure Cosmos DB SQL API

After completing this module, students will be able to:

  • Process change feed events using the SDK
  • Implement change feed best practices
  • Create an Azure Functions trigger for Azure Cosmos DB
  • Create an Azure Functions input for Azure Cosmos DB
  • Index Azure Cosmos DB data in Azure Cognitive Search

Module 8: Implement a data modeling and partitioning strategy for Azure Cosmos DB SQL API

Azure Cosmos DB is both horizontally scalable and nonrelational. To achieve this level of scalability, users need to understand the concepts, techniques, and technologies unique to NoSQL databases for modeling and partitioning data. In this module, you will model and partition data appropriately for a NoSQL database such as Azure Cosmos DB SQL API.

Lessons

  • Model and partition your data in Azure Cosmos DB
  • Optimize databases by using advanced modeling patterns for Azure Cosmos DB

Lab: Exercise: Measure performance for customer entities

Lab: Exercise: Advanced modeling patterns

After completing this module, students will be able to:

  • Identify application access patterns for an existing application
  • Decide when to embed or reference data
  • Use change feed to manage referential integrity
  • Combine multiple entities in a single container
  • Denormalize aggregated data in a single container

Module 9: Design and implement a replication strategy for Azure Cosmos DB SQL API

Today's applications are required to be highly responsive and always online. To achieve low latency and high availability, instances of these applications need to be deployed in datacenters that are close to their users. In this module, you will explore how to replicate data and manage consistency across the globe using Azure Cosmos DB SQL API.

Lessons

  • Configure replication and manage failovers in Azure Cosmos DB
  • Use consistency models in Azure Cosmos DB SQL API
  • Configure multi-region write in Azure Cosmos DB SQL API

Lab: Exercise: Configure consistency models in the portal and the Azure Cosmos DB SQL API SDK

Lab: Exercise: Connect to different regions with the Azure Cosmos DB SQL API SDK

Lab: Exercise: Connect to a multi-region write account with the Azure Cosmos DB SQL API SDK

After completing this module, students will be able to:

  • Distribute data across various geographies
  • Define automatic failover policies
  • Perform manual failovers
  • Configure default consistency model
  • Change per-session consistency model
  • Configure multi-region write in the SDK
  • Create a custom conflict resolution policy

Module 10: Optimize query performance in Azure Cosmos DB SQL API

Azure Cosmos DB offers a rich set of database operations that operate on the items within a container. The cost associated with each of these operations varies based on the CPU, IO, and memory required to complete the operation. In this module, you will explore how to manage indexing policies and edit queries to minimize per-query request unit (RU) cost.

Lessons

  • Choosing indexes in Azure Cosmos DB SQL API
  • Optimize queries in Azure Cosmos DB SQL API
  • Implement integrated cache

Lab: Exercise: Optimize an Azure Cosmos DB SQL API container's index policy for common operations

Lab: Exercise: Optimize an Azure Cosmos DB SQL API container's index policy for a specific query

After completing this module, students will be able to:

  • Review and compare read-heavy vs. write-heavy index patterns
  • Update indexing policy to optimize index performance
  • Measure cost of a query in request units (RUs)
  • Measure cost of point operations
  • Work with item and query integrated cache
  • Configure integrated cache staleness

Module 11: Administrating and Monitoring tasks for an Azure Cosmos DB SQL API solution

When you have critical applications and business processes relying on Azure resources such as Azure Cosmos DB, you want to monitor those resources for their availability, performance, and operation. In this module, you will explore how to monitor events and performance of an Azure Cosmos DB account. You will also learn how to implement common security measures along with backup and restore in Azure Cosmos DB.

Lessons

  • Measure performance in Azure Cosmos DB SQL API
  • Monitor responses and events in Azure Cosmos DB SQL API
  • Implementing backup and restore for Azure Cosmos DB SQL API
  • Implement security in Azure Cosmos DB SQL API

Lab: Exercise: Troubleshoot an application using the Azure Cosmos DB SQL API SDK

Lab: Exercise: Use Azure Monitor to analyze an Azure Cosmos DB SQL API account

Lab: Exercise: Recover a database or container from a recovery point

Lab: Exercise: Store Azure Cosmos DB SQL API account keys in Azure Key Vault

After completing this module, students will be able to:

  • Observe rate-limiting events in a container or database
  • Query resource logs using Azure Monitor
  • Review and observe transient and rate-limiting errors
  • Configure alerts
  • Configure continuous backup and recovery
  • Perform a point-in-time recovery
  • Use role-based access control (RBAC)
  • Access account resources using Azure AD and Microsoft Identity Platform

Module 12: Manage an Azure Cosmos DB SQL API solution using DevOps practices

Once an Azure Cosmos DB SQL API account is ready to go through a release lifecycle, it's common for an operations team to attempt to automate the creation of Azure Cosmos DB resources in the cloud. Automation makes it easier to deploy new environments, restore past environments, or scale a service out. In this module, you will explore how to use Azure Resource Manager to manage an Azure Cosmos DB account and its child resources using JSON templates, Bicep templates, or the Azure CLI.

Lessons

  • Write scripts for Azure Cosmos DB SQL API
  • Create resource template for Azure Cosmos DB SQL API

Lab: Exercise: Adjust provisioned throughput using an Azure CLI script

Lab: Exercise: Create an Azure Cosmos DB SQL API container using Azure Resource Manager templates

After completing this module, students will be able to:

  • View arguments, groups, and subgroups for a specific CLI command
  • Create Azure Cosmos DB accounts, databases, and containers using the CLI
  • Manage an indexing policy using the CLI
  • Configure database or container throughput using the CLI
  • Initiate failovers and manage failover regions using the CLI
  • Identify the three most common resource types for Azure Cosmos DB SQL API accounts
  • Create and deploy a JSON Azure Resource Manager template for Azure Cosmos DB SQL API
  • Create and deploy a Bicep Azure Resource Manager template for Azure Cosmos DB SQL API
  • Manage throughput and index policies using JSON or Bicep templates

Module 13: Create server-side programming constructs in Azure Cosmos DB SQL API

Azure Cosmos DB provides language-integrated, transactional execution of JavaScript. When using the SQL API in Azure Cosmos DB, you can write stored procedures, triggers, and user-defined functions (UDFs) in the JavaScript language. In this module, you will author JavaScript logic that executes directly inside the database engine.

Lessons

  • Build multi-item transactions with the Azure Cosmos DB SQL API
  • Expand query and transaction functionality in Azure Cosmos DB SQL API

Lab: Exercise: Implement and then use a UDF using the SDK

Lab: Exercise: Create a stored procedure with the Azure Portal

After completing this module, students will be able to:

  • Author stored procedure
  • Rollback stored procedure transaction
  • Create UDF
  • Create pre-* and post-* triggers

Show moredown

Who should attend this Microsoft training course?

Software engineers tasked with authoring cloud-native solutions that leverage Azure Cosmos DB SQL API and its various SDKs. They are familiar with C#, Python, Java, or JavaScript. They also have experience writing code that interacts with a SQL or NoSQL database platform.

  • Job role: Developer.
  • Preparation for exam: DP-420.

Prerequisites

Before attending this course, students must have:

  • Knowledge of Microsoft Azure and ability to navigate the Azure portal (AZ-900 equivalent).
  • Experience writing in an Azure-supported language at the intermediate level. (C#, JavaScript, Python, or Java).
  • Ability to write code to connect and perform operations on a SQL or NoSQL database product. (SQL Server, Oracle, MongoDB, Cassandra or similar).

Designing and Implementing CloudNative Applications Using Microsoft Azure Cosmos DB DP420 Course Overview

This course teaches developers how to create application using the SQL API and SDK for Azure Cosmos DB. Students will learn how to write efficient queries, create indexing policies, manage and provisioned resources, and perform common operations with the SDK.

What will you gain from taking this Microsoft training course?

  • Create and configure Azure Cosmos DB SQL API account, database, and container.
  • Use the .NET SDK to manage resources and perform operations.
  • Perform queries of varying complexity.
  • Design a data modeling and partitioning strategy.
  • Optimize queries and indexes based on characteristics of an application.
  • Use the Azure Resource Manager to manage accounts and resources with CLI or JSON and Bicep templates.

Show moredown

What's included in this Microsoft training course?

  • Delegate pack consisting of course notes and exercises.
  • Manual.
  • Experienced Instructor.

Show moredown

accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (4 days)

Online Self-paced (32 hours)

Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI DP500 Course Outline

Within this training course you will learn the following modules.

Module 1: Introduction to data analytics on Azure

This module explores key concepts of data analytics, including types of analytics, data, and storage. Students will explore the analytics process and tools used to discover insights and learn about the responsibilities of an enterprise data analyst and what tools are available to build scalable solutions.

Lessons

  • Explore Azure data services for modern analytics
  • Understand concepts of data analytics
  • Explore data analytics at scale

After completing this module, students will be able to:

  • Describe types of data analytics
  • Understand the data analytics process
  • Define data job roles in analytics
  • Understand tools for scaling analytics solutions

Module 2: Govern data across an enterprise

This module explores the role of an enterprise data analyst in organizational data governance. Students will explore the use of Microsoft Purview to register and catalog data assets, to discover trusted assets for reporting, and to scan a Power BI environment.

Lessons

  • Introduction to Microsoft Purview
  • Discover trusted data using Microsoft Purview
  • Catalog data artifacts by using Microsoft Purview
  • Manage Power BI artifacts by using Microsoft Purview

After completing this module, students will be able to:

  • Browse, search, and manage data catalog assets.
  • Use data catalog assets with Power BI.
  • Use Microsoft Purview in Azure Synapse Studio.
  • Register and scan a Power BI environment using Microsoft Purview.

Module 3: Model, query, and explore data in Azure Synapse

This module explores the use of Azure Synapse Analytics for exploratory data analysis. Students will explore the capabilities of Azure Synapse Analytics including the basics of data warehouse design, querying data using T-SQL, and exploring data using Spark notebooks.

Lessons

  • Introduction to Azure Synapse Analytics
  • Use Azure Synapse serverless SQL pool to query files in a data lake
  • Analyze data with Apache Spark in Azure Synapse Analytics
  • Analyze data in a relational data warehouse

Lab: Query data in Azure

Lab: Create a star schema model

Lab: Explore data in Spark notebooks

After completing this module, students will be able to:

  • Understand when to use Azure Synapse Analytics in reporting solutions.
  • Query data with SQL.
  • Query data with Spark.

Module 4: Prepare data for tabular models in Power BI

This module explores the fundamental elements of preparing data for scalable analytics solutions using Power BI. Students will explore model frameworks, considerations for building data models that will scale, Power Query optimization techniques, and the implementation of Power BI dataflows.

Lessons

  • Choose a Power BI model framework
  • Understand scalability in Power BI
  • Optimize Power Query for scalable solutions
  • Create and manage scalable Power BI dataflows

Lab: Create a dataflow

After completing this module, students will be able to:

  • Choose an appropriate Power BI model framework.
  • Optimize Power Query.
  • Create and manage scalable Power BI dataflows.

Module 5: Design and build scalable tabular models

This module explores the critical underlying aspects of tabular modeling for building Power BI models that can scale. Students will learn about model relationships and model security, working with direct query, and using calculation groups.

Lessons

  • Create Power BI model relationships
  • Enforce model security
  • Implement DirectQuery
  • Create calculation groups
  • Use tools to optimize Power BI performance

Lab: Create model relationships

Lab: Design and build tabular models

Lab: Create calculation groups

Lab: Use tools to optimize Power BI performance

Lab: Enforce model security

After completing this module, students will be able to:

  • Understand and create Power BI model relationships.
  • Design and enforce Power BI model security.
  • Design and build scalable tabular models.
  • Create calculation groups.

Module 6: Implement advanced data visualization techniques by using Power BI

This module explores data visualization concepts including accessibility, customization of core data models, real-time data visualization, and paginated reporting.

Lessons

  • Understand advanced data visualization concepts
  • Customize core data models
  • Monitor data in real-time with Power BI
  • Create and distribute paginated reports in Power BI report builder

Lab: Create and distribute paginated reports in Power BI Report Builder

Lab: Monitor data in real-time with Power BI

After completing this module, students will be able to:

  • Understand and apply advanced data visualization concepts including accessibility.
  • Troubleshoot report performance issues.
  • Use real-time visuals in Power BI.
  • Create and distribute paginated reports.

Module 7: Implement and manage an analytics environment

This module explores key considerations for implementing and managing Power BI. Students will understand key recommendations for administration and monitoring of Power BI, including configuration and management of Power BI capacity.

Lessons

  • Provide governance in a Power BI environment
  • Facilitate collaboration and sharing in Power BI
  • Monitor and audit usage
  • Provision Premium capacity in Power BI
  • Establish a data access infrastructure in Power BI
  • Broaden the reach of Power BI
  • Automate Power BI administration
  • Build reports using Power BI within Azure Synapse Analytics

After completing this module, students will be able to:

  • Recommend Power BI administration settings.
  • Recommend a monitoring and auditing solution for a data analytics environment.
  • Configure and manage Power BI capacity.

Module 8: Manage the analytics development lifecycle

This module explores considerations for deployment, source control, and application lifecycle management of analytics solutions. Students will understand what to recommend and will be able to deploy and manage automated and reusable Power BI assets.

Lessons

  • Design a Power BI application lifecycle management strategy
  • Create and manage a Power BI deployment pipeline
  • Create and manage Power BI assets

Lab: Create reusable Power BI assets

After completing this module, students will be able to:

  • Recommend strategies for Power BI deployment and source control.
  • Recommend automation solutions for the analytics development lifecycle.

Module 9: Integrate an analytics platform into an existing IT infrastructure

This module explores the integration of a Power BI analytics solution into existing Azure infrastructure. Students will understand Power BI tenant and workspace configurations, along with considerations for Power BI deployment in an organization.

Lessons

  • Recommend and configure a Power BI tenant or workspace
  • Identify requirements for a solution, including features, performance, and licensing strategy
  • Integrate an existing Power BI workspace into Azure Synapse Analytics

After completing this module, students will be able to:

  • Recommend and configure a Power BI tenant or workspace.
  • Identify requirements for a solution, including features, performance, and licensing strategy.
  • Integrate an existing Power BI workspace into Azure Synapse Analytics.

Show moredown

Who should attend this Microsoft training course?

Candidates for this course should have subject matter expertise in designing, creating, and deploying enterprise-scale data analytics solutions. Specifically, candidates should have advanced Power BI skills, including managing data repositories and data processing in the cloud and on-premises, along with using Power Query and Data Analysis Expressions (DAX). They should also be proficient in consuming data from Azure Synapse Analytics and should have experience querying relational databases, analyzing data by using Transact-SQL (T-SQL), and visualizing data.

  • Job role: Data Analyst
  • Preparation for exam: DP-500

Prerequisites

It is recommended that students have:

  • A foundational knowledge of core data concepts and how they’re implemented using Azure data services. For more information see Azure Data Fundamentals.
  • Experience designing and building scalable data models, cleaning, and transforming data, and enabling advanced analytic capabilities that provide meaningful business value using Microsoft Power BI. For more information see Power BI Data Analyst.

Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI DP500 Course Overview

This course covers methods and practices for performing advanced data analytics at scale. Students will build on existing analytics experience and will learn to implement and manage a data analytics environment, query, and transform data, implement, and manage data models, and explore and visualize data. In this course, students will use Microsoft Purview, Azure Synapse Analytics, and Power BI to build analytics solutions.

What will you gain from this training course?

  • Implement and manage a data analytics environment
  • Query and transform data
  • Implement and manage data models
  • Explore and visualize data

Show moredown

What's included within this Microsoft training course?

  • Experienced Instructor
  • Labs

Show moredown

accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (4 days)

Online Self-paced (32 hours)

Planning and Administering Microsoft Azure for SAP Workloads Course Outline | MAZ120

Module 1: Introduction to Azure for SAP Workloads

  • Partnership Between Microsoft and SAP
  • Introduction to Azure for SAP workloads
  • How to Evaluate Microsoft Components?
  • Common Terms and Meanings

Module 2: Foundations of Azure for SAP Workloads

  • Contains Lessons on Azure Compute
  • Azure Storage
  • Azure Networking
  • Identity Services
  • Governance and Manageability

Module 3: SAP Certified Offerings On Azure

  • General Prerequisites (SAP Support in Public Cloud Environments)
  • Deployment Options of Azure for SAP Workloads
  • SAP Product-Specific Support for Azure
  • Operating System Support of Azure for SAP Workloads
  • Storage Support of Azure for SAP Workloads
  • Networking Support for SAP
  • Database Support for SAP
  • High Availability and Disaster Recovery Support for SAP
  • Monitoring Requirements for SAP

Lab: Online Lab: Implementing Linux Clustering on Azure VMs

Lab: Online Lab: Implementing Windows Clustering on Azure VMs

Module 4: Azure for SAP Workloads Reference Architecture

  • Lessons on SAP NetWeaver with AnyDB on Azure VMs
  • SAP S4 HANA on Azure VMs

Module 5: Planning for Implementing SAP Solutions on Azure

  • Azure VM Compute, Network, and Storage Considerations
  • Azure VM high Availability and Disaster Recovery Considerations
  • Azure VM Backup, Monitoring, and Security Considerations
  • Azure VM Authentication and Access Control Considerations  
  • Azure VM Licensing, Pricing, and Support Considerations

Module 6: Planning for Migrating SAP Workloads to Azure

  • Strategies for Migrating SAP Systems to Microsoft Azure
  • SAP a Workload Planning and Deployment Checklist

Module 7: Implementing Azure VM-Based SAP Solutions

  • Azure VM Deployment Methodologies
  • Single-Instance Implementations (2-tier and 3-tier)
  • Implementing HA SAP NetWeaver with AnyDB on Azure VMs
  • Implementing HA SAP HANA on Azure VMs
  • Configuring Azure Enhanced Monitoring Extension for SAP
  • Implementing AD and Azure AD-Based Authentication

Lab: Online Lab: Implementing SAP Architecture on Azure VMs Running Windows

Lab: Online Lab: Implementing SAP Architecture on Azure VMs Running Linux

Module 8: SAP HANA on Azure (Large Instances) (HLI)

  • Foundations of SAP HANA on Azure (Large Instances) (HLI)
  • HLI Certified Offerings and Sample Architecture
  • HLI Planning Considerations
  • HLI High Availability and Disaster Recovery Planning
  • HLI Backup and Security Considerations
  • HLI Licensing and Support
  • Implementing, Deploying, and Managing HLI
  • HLI Monitoring and Troubleshooting

Module 9: Migrating SAP Workloads to Azure

  • Migration Options
  • DMO Methodology
  • Cloud Migration Options
  • Very Large Database Migration to Azure

Module 10: Maintaining Azure for SAP Workloads

  • Remote Management
  • Performing Backups and Restores
  • Networking Changes
  • OS and Workload Updates
  • Vertical and Horizontal Scaling
  • Disaster Recovery

Module 11: Monitoring and Troubleshooting Azure for SAP Workloads

  • Monitoring and Troubleshooting Azure VMs
  • Raising Support Requests

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Who should attend this Azure Training Course?

This course is for Azure Administrators who migrate and manage SAP solutions on Azure. Azure Administrators manage the cloud services that span storage, networking and compute cloud capabilities, with a deep understanding of each service across the full IT lifecycle. They take end-user requests for new cloud applications and make recommendations on services to use for optimal performance and scale, as well as provision, size, monitor and adjust as appropriate. This role requires communicating and coordinating with vendors. Azure Administrators use the Azure Portal and as they become more proficient they use PowerShell and the Command Line Interface.

AZ-120 Prerequisites

  • Administrators and architects of Azure solutions for SAP should possess solid knowledge of SAP Applications, SAP HANA, S/4HANA, SAP NetWeaver, SAP BW, OS Servers for SAP Applications and Databases.
  • Prior to taking this course, it is recommended that students to have taken the Azure Administrator (AZ-103) or Azure Solutions Architect (AZ-300) training, as well as SAP HANA and Linux training.

Planning and Administering Microsoft Azure for SAP Workloads Course Overview | MAZ120

This course teaches IT Professionals experienced in SAP solutions how to leverage Azure resources that include deployment and configuration of virtual machines, virtual networks, storage accounts, and Azure AD that includes implementing and managing hybrid identities. Students of this course will learn through concepts, scenarios, procedures, and hands-on labs on how to best plan and implement migration and operation of an SAP solution on Azure. You will receive guidance on subscriptions, create and scale virtual machines, implement storage solutions, configure virtual networking, back up and share data, connect Azure and on-premises sites, manage network traffic, implement Azure Active Directory, secure identities,

After completing this course, students will be able to:

  • Migrate and SAP HANA, S/4HANA, SAP NetWeaver to Azure
  • Leverage Azure Portal, Cloud Shell, Azure PowerShell, CLI, and Resource Manager
  • Use intersite connectivity features including VNet Peering and VNet-to-VNet connections
  • Work with Azure Active Directory (AAD) and Azure AD Connect

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What's included in this Azure Training Course?

  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor
  • Refreshments

AZ-120 Exam Information:

  • Migrate SAP Workloads to Azure (10-15%)
  • Design an Azure Solution to Support SAP Workloads (20-25%)
  • Build and Deploy Azure SAP Workloads (35-40%)
  • Validate Azure Infrastructure for SAP Workloads (10-15%)
  • Operationalize Azure SAP Architecture (10-15%)

Please Note: The Exam isn't included within the cost of this 4-day training course.

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accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (4 days)

Online Self-paced (32 hours)

AZ-800: Administering Windows Server Hybrid Core Infrastructure

Administering Windows Server Hybrid Core Infrastructure AZ800 Course Outline

Module 1: Identity services in Windows Server

This module introduces identity services and describes Active Directory Domain Services (AD DS) in a Windows Server environment. The module describes how to deploy domain controllers in AD DS, as well as Azure Active Directory (AD) and the benefits of integrating Azure AD with AD DS. The module also covers Group Policy basics and how to configure group policy objects (GPOs) in a domain environment.

Lessons

  • Introduction to AD DS
  • Manage AD DS domain controllers and FSMO roles
  • Implement Group Policy Objects
  • Manage advanced features of AD DS

Lab : Implementing identity services and Group Policy

  • Deploying a new domain controller on Server Core
  • Configuring Group Policy

After completing this module, students will be able to:

  • Describe AD DS in a Windows Server environment.
  • Deploy domain controllers in AD DS.
  • Describe Azure AD and benefits of integrating Azure AD with AD DS.
  • Explain Group Policy basics and configure GPOs in a domain environment.

Module 2: Implementing identity in hybrid scenarios

This module discusses how to configure an Azure environment so that Windows IaaS workloads requiring Active Directory are supported. The module also covers integration of on-premises Active Directory Domain Services (AD DS) environment into Azure. Finally, the module explains how to extend an existing Active Directory environment into Azure by placing IaaS VMs configured as domain controllers onto a specially configured Azure virtual network subnet.

Lessons

  • Implement hybrid identity with Windows Server
  • Deploy and manage Azure IaaS Active Directory domain controllers in Azure

Lab : Implementing integration between AD DS and Azure AD

  • Preparing Azure AD for AD DS integration
  • Preparing on-premises AD DS for Azure AD integration
  • Downloading, installing, and configuring Azure AD Connect
  • Verifying integration between AD DS and Azure AD
  • Implementing Azure AD integration features in AD DS

After completing this module, students will be able to:

  • Integrate on-premises Active Directory Domain Services (AD DS) environment into Azure.
  • Install and configure directory synchronization using Azure AD Connect.
  • Implement and configure Azure AD DS.
  • Implement Seamless Single Sign-on (SSO).
  • Implement and configure Azure AD DS.
  • Install a new AD DS forest on an Azure VNet.

Module 3: Windows Server administration

This module describes how to implement the principle of least privilege through Privileged Access Workstation (PAW) and Just Enough Administration (JEA). The module also highlights several common Windows Server administration tools, such as Windows Admin Center, Server Manager, and PowerShell. This module also describes the post-installation configuration process and tools available to use for this process, such as sconfig and Desired State Configuration (DSC).

Lessons

  • Perform Windows Server secure administration
  • Describe Windows Server administration tools
  • Perform post-installation configuration of Windows Server
  • Just Enough Administration in Windows Server

Lab : Managing Windows Server

  • Implementing and using remote server administration

After completing this module, students will be able to:

  • Explain least privilege administrative models.
  • Decide when to use privileged access workstations.
  • Select the most appropriate Windows Server administration tool for a given situation.
  • Apply different methods to perform post-installation configuration of Windows Server.
  • Constrain privileged administrative operations by using Just Enough Administration (JEA).

Module 4: Facilitating hybrid management

This module covers tools that facilitate managing Windows IaaS VMs remotely. The module also covers how to use Azure Arc with on-premises server instances, how to deploy Azure policies with Azure Arc, and how to use role-based access control (RBAC) to restrict access to Log Analytics data.

Lessons

  • Administer and manage Windows Server IaaS virtual machines remotely
  • Manage hybrid workloads with Azure Arc

Lab : Using Windows Admin Center in hybrid scenarios

  • Provisioning Azure VMs running Windows Server
  • Implementing hybrid connectivity by using the Azure Network Adapter
  • Deploying Windows Admin Center gateway in Azure
  • Verifying functionality of the Windows Admin Center gateway in Azure

After completing this module, students will be able to:

  • Select appropriate tools and techniques to manage Windows IaaS VMs remotely.
  • Explain how to onboard on-premises Windows Server instances in Azure Arc.
  • Connect hybrid machines to Azure from the Azure portal.
  • Use Azure Arc to manage devices.
  • Restrict access using RBAC.

Module 5: Hyper-V virtualization in Windows Server

This module describes how to implement and configure Hyper-V VMs and containers. The module covers key features of Hyper-V in Windows Server, describes VM settings, and how to configure VMs in Hyper-V. The module also covers security technologies used with virtualization, such as shielded VMs, Host Guardian Service, admin-trusted and TPM-trusted attestation, and Key Protection Service (KPS). Finally, this module covers how to run containers and container workloads, and how to orchestrate container workloads on Windows Server using Kubernetes.

Lessons

  • Configure and manage Hyper-V
  • Configure and manage Hyper-V virtual machines
  • Secure Hyper-V workloads
  • Run containers on Windows Server
  • Orchestrate containers on Windows Server using Kubernetes

Lab : Implementing and configuring virtualization in Windows Server

  • Creating and configuring VMs
  • Installing and configuring containers

After completing this module, students will be able to:

  • Install and configure Hyper-V on Windows Server.
  • Configure and manage Hyper-V virtual machines.
  • Use Host Guardian Service to protect virtual machines.
  • Create and deploy shielded virtual machines.
  • Configure and manage container workloads.
  • Orchestrate container workloads using a Kubernetes cluster.

Module 6: Deploying and configuring Azure VMs

This module describes Azure compute and storage in relation to Azure VMs, and how to deploy Azure VMs by using the Azure portal, Azure CLI, or templates. The module also explains how to create new VMs from generalized images and use Azure Image Builder templates to create and manage images in Azure. Finally, this module describes how to deploy Desired State Configuration (DSC) extensions, implement those extensions to remediate noncompliant servers, and use custom script extensions.

Lessons

  • Plan and deploy Windows Server IaaS virtual machines
  • Customize Windows Server IaaS virtual machine images
  • Automate the configuration of Windows Server IaaS virtual machines

Lab : Deploying and configuring Windows Server on Azure VMs

  • Authoring Azure Resource Manager (ARM) templates for Azure VM deployment
  • Modifying ARM templates to include VM extension-based configuration
  • Deploying Azure VMs running Windows Server by using ARM templates
  • Configuring administrative access to Azure VMs running Windows Server
  • Configuring Windows Server security in Azure VMs

After completing this module, students will be able to:

  • Create a VM from the Azure portal and from Azure Cloud Shell.
  • Deploy Azure VMs by using templates.
  • Automate the configuration of Windows Server IaaS VMs.
  • Detect and remediate noncompliant servers.
  • Create new VMs from generalized images.
  • Use Azure Image Builder templates to create and manage images in Azure.

Module 7: Network infrastructure services in Windows Server

This module describes how to implement core network infrastructure services in Windows Server, such as DHCP and DNS. This module also covers how to implement IP address management and how to use Remote Access Services.

Lessons

  • Deploy and manage DHCP
  • Implement Windows Server DNS
  • Implement IP address management
  • Implement remote access

Lab : Implementing and configuring network infrastructure services in Windows Server

  • Deploying and configuring DHCP
  • Deploying and configuring DNS

After completing this module, students will be able to:

  • Implement automatic IP configuration with DHCP in Windows Server.
  • Deploy and configure name resolution with Windows Server DNS.
  • Implement IPAM to manage an organization’s DHCP and DNS servers, and IP address space.
  • Select, use, and manage remote access components.
  • Implement Web Application Proxy (WAP) as a reverse proxy for internal web applications.

Module 8: Implementing hybrid networking infrastructure

This module describes how to connect an on-premises environment to Azure and how to configure DNS for Windows Server IaaS virtual machines. The module covers how to choose the appropriate DNS solution for your organization’s need and run a DNS server in a Windows Server Azure IaaS VM. Finally, this module covers how to manage Microsoft Azure virtual networks and IP address configuration for Windows Server infrastructure as a service (IaaS) virtual machines.

Lessons

  • Implement hybrid network infrastructure
  • Implement DNS for Windows Server IaaS VMs
  • Implement Windows Server IaaS VM IP addressing and routing

Lab : Implementing Windows Server IaaS VM networking

  • Implementing virtual network routing in Azure
  • Implementing DNS name resolution in Azure

After completing this module, students will be able to:

  • Implement an Azure virtual private network (VPN).
  • Configure DNS for Windows Server IaaS VMs.
  • Run a DNS server in a Windows Server Azure IaaS VM.
  • Create a route-based VPN gateway using the Azure portal.
  • Implement Azure ExpressRoute.
  • Implement an Azure wide area network (WAN).
  • Manage Microsoft Azure virtual networks (VNets).
  • Manage IP address configuration for Windows Server IaaS virtual machines (VMs).

Module 9: File servers and storage management in Windows Server

This module covers the core functionality and use cases of file server and storage management technologies in Windows Server. The module discusses how to configure and manage the Windows File Server role, and how to use Storage Spaces and Storage Spaces Direct. This module also covers replication of volumes between servers or clusters using Storage Replica.

Lessons

  • Manage Windows Server file servers
  • Implement Storage Spaces and Storage Spaces Direct
  • Implement Windows Server Data Deduplication
  • Implement Windows Server iSCSI
  • Implement Windows Server Storage Replica

Lab : Implementing storage solutions in Windows Server

  • Implementing Data Deduplication
  • Configuring iSCSI storage
  • Configuring redundant Storage Spaces
  • Implementing Storage Spaces Direct

After completing this module, students will be able to:

  • Configure and manage the Windows Server File Server role.
  • Protect data from drive failures using Storage Spaces.
  • Increase scalability and performance of storage management using Storage Spaces Direct.
  • Optimize disk utilization using Data DeDuplication.
  • Configure high availability for iSCSI.
  • Enable replication of volumes between clusters using Storage Replica.
  • Use Storage Replica to provide resiliency for data hosted on Windows Servers volumes.

Module 10: Implementing a hybrid file server infrastructure

This module introduces Azure file services and how to configure connectivity to Azure Files. The module also covers how to deploy and implement Azure File Sync to cache Azure file shares on an on-premises Windows Server file server. This module also describes how to manage cloud tiering and how to migrate from DFSR to Azure File Sync.

Lessons

  • Overview of Azure file services
  • Implementing Azure File Sync

Lab : Implementing Azure File Sync

  • Implementing DFS Replication in your on-premises environment
  • Creating and configuring a sync group
  • Replacing DFS Replication with File Sync–based replication
  • Verifying replication and enabling cloud tiering
  • Troubleshooting replication issues

After completing this module, students will be able to:

  • Configure Azure file services.
  • Configure connectivity to Azure file services.
  • Implement Azure File Sync.
  • Deploy Azure File Sync
  • Manage cloud tiering.
  • Migrate from DFSR to Azure File Sync.

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Audience Profile

This four-day course is intended for Windows Server Hybrid Administrators who have experience working with Windows Server and want to extend the capabilities of their on-premises environments by combining on-premises and hybrid technologies. Windows Server Hybrid Administrators implement and manage on-premises and hybrid solutions such as identity, management, compute, networking, and storage in a Windows Server hybrid environment.

Prerequisites

Before attending this course, students must have:

  • Experience with managing Windows Server operating system and Windows Server workloads in on-premises scenarios, including AD DS, DNS, DFS, Hyper-V, and File and Storage Services
  • Experience with common Windows Server management tools (implied in the first prerequisite).
  • Basic knowledge of core Microsoft compute, storage, networking, and virtualization technologies (implied in the first prerequisite).
  • Experience and an understanding of core networking technologies such as IP addressing, name resolution, and Dynamic Host Configuration Protocol (DHCP)
  • Experience working with and an understanding of Microsoft Hyper-V and basic server virtualization concepts
  • Basic experience with implementing and managing IaaS services in Microsoft Azure
  • Basic knowledge of Azure Active Directory
  • Experience working hands-on with Windows client operating systems such as Windows 10 or Windows 11
  • Basic experience with Windows PowerShell

Administering Windows Server Hybrid Core Infrastructure AZ800 Course Overview

This course teaches IT Professionals how to manage core Windows Server workloads and services using on-premises, hybrid, and cloud technologies. The course teaches IT Professionals how to implement and manage on-premises and hybrid solutions such as identity, management, compute, networking, and storage in a Windows Server hybrid environment.

Skills gained

  • Use administrative techniques and tools in Windows Server.
  • Identify tools used to implement hybrid solutions, including Windows Admin Center and PowerShell.
  • Implement identity services in Windows Server.
  • Implement identity in hybrid scenarios, including Azure AD DS on Azure IaaS and managed AD DS.
  • Integrate Azure AD DS with Azure AD.
  • Manage network infrastructure services.
  • Deploy Azure VMs running Windows Server and configure networking and storage.
  • Administer and manage Windows Server IaaS Virtual Machine remotely.
  • Manage and maintain Azure VMs running Windows Server.
  • Configure file servers and storage.
  • Implement File Services in hybrid scenarios, using Azure Files and Azure File Sync.

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Exam AZ-800: Administering Windows Server Hybrid Core Infrastructure Information

  • Deploy and manage Active Directory Domain Services (AD DS) in on-premises and cloud environments (30—35%)
  • Manage Windows Servers and workloads in a hybrid environment (10—15%)
  • Manage virtual machines and containers (15—20%)
  • Implement and manage an on-premises and hybrid networking infrastructure (15—20%)
  • Manage storage and file services (15—20%)

Passing Score: 700

Candidates for this exam are responsible for configuring and managing Windows Server on-premises, hybrid, and Infrastructure as a Service (IaaS) platform workloads. The Windows Server hybrid administrator is tasked with integrating Windows Server environments with Azure services and managing Windows Server in on-premises networks. This role manages and maintains Windows Server IaaS workloads in Azure as well as migrating and deploying workloads to Azure. This role typically collaborates with Azure administrators, enterprise architects, Microsoft 365 administrators, and network engineers.

Candidates for this exam deploy, package, secure, update, and configure Windows Server workloads using on-premises, hybrid, and cloud technologies. This role implements and manages on-premises and hybrid solutions, such as identity, security, management, compute, networking, storage, monitoring, high availability, and disaster recovery. This role uses administrative tools and technologies such as Windows Admin Center, PowerShell, Azure Arc, Azure Policy, Azure Monitor, Azure Automation Update Management, Microsoft Defender for Identity, Microsoft Defender for Cloud, and IaaS VM administration.

Candidates for this exam have several years of experience with Windows Server operating systems.

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accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (4 days)

Online Self-paced (32 hours)

Microsoft Azure Administrator MAZ104 Course Outline

Within this Microsoft Azure training course, you will learn the following modules:

Module 1: Identity

In this module, you will learn how to secure identities with Azure Active Directory and implement users and groups.

Lessons

  • Azure Active Directory
  • Users and Groups

Lab: Manage Azure Active Directory Identities

After completing this module, students will be able to:

  • Secure and manage identities with Azure Active Directory.
  • Implement and manage users and groups.

Module 2: Governance and Compliance

In this module, you will learn about managing your subscriptions and accounts, implementing Azure policies, and using Role-Based Access Control.

Lessons

  • Subscriptions and Accounts
  • Azure Policy
  • Role-based Access Control (RBAC)

Lab: Manage Subscriptions and RBAC

Lab: Manage Governance via Azure Policy

After completing this module, students will be able to:

  • Implement and manage Azure subscriptions and accounts.

  • Implement Azure Policy, including custom policies.

  • Use RBAC to assign permissions.

Module 3: Azure Administration

In this module, you will learn about the tools an Azure Administrator uses to manage their infrastructure. This includes the Azure Portal, Cloud Shell, Azure PowerShell, CLI, and Resource Manager Templates. This module includes:

Lessons

  • Azure Administrator Tools
  • ARM Templates

Lab: Manage Azure resources by Using ARM Templates

Lab: Manage Azure resources by Using Azure PowerShell (optional)

Lab: Manage Azure resources by Using Azure CLI (optional)

Lab: Manage Azure resources by Using the Azure Portal

After completing this module, students will be able to:

  • Use the Azure Portal and Cloud Shell.
  • Use Azure PowerShell and CLI.
  • Use ARM Templates to deploy resources.

Module 4: Virtual Networking

In this module, you will learn about basic virtual networking concepts like virtual networks and subnetting, IP addressing, network security groups, Azure Firewall, and Azure DNS.

Lessons

  • Virtual Networks
  • Network Security groups
  • Azure Firewall
  • Azure DNS

Lab: Implement Virtual Networking

After completing this module, students will be able to:

  • Implement virtual networks and subnets.
  • Configure network security groups.
  • Configure Azure Firewall.
  • Configure private and public DNS zones.

Module 5: Intersite Connectivity

In this module, you will learn about intersite connectivity features including VNet Peering, Virtual Network Gateways, and Site-to-Site Connections.

Lessons

  • VNet Peering
  • VPN Gateway Connections
  • ExpressRoute and Virtual WAN

Lab: Implement Intersite Connectivity

After completing this module, students will be able to:

  • Configure VNet Peering.
  • Configure VPN gateways.
  • Choose the appropriate intersite connectivity solution.

Module 6: Network Traffic Management

In this module, you will learn about network traffic strategies including network routing and service endpoints, Azure Load Balancer, and Azure Application Gateway.

Lessons

  • Network Routing and Endpoints
  • Azure Load Balancer
  • Azure Application Gateway
  • Network Watcher

Lab: Implement Traffic Management

After completing this module, students will be able to:

  • Configure network routing including custom routes and service endpoints.
  • Configure an Azure Load Balancer.
  • Configure an Azure Application Gateway.
  • Configure Network Watcher.

Module 7: Azure Storage

In this module, you will learn about basic storage features including storage accounts, blob storage, Azure files and File Sync, storage security, and storage tools.

Lessons

  • Storage Accounts
  • Blob Storage
  • Storage Security
  • Azure Files and File Sync
  • Managing Storage

Lab: Manage Azure storage

After completing this module, students will be able to:

  • Create Azure storage accounts.
  • Configure blob containers.
  • Secure Azure storage.
  • Configure Azure files shares and file sync.
  • Manage storage with tools such as Storage Explorer.

Module 8: Azure Virtual Machines

In this module, you will learn about Azure virtual machines including planning, creating, availability and extensions.

Lessons

  • Creating Virtual Machines
  • Virtual Machine Availability
  • Virtual Machine Extensions

Lab: Manage virtual machines

After completing this module, students will be able to:

  • Plan for virtual machine implementations.
  • Create virtual machines.
  • Configure virtual machine availability, including scale sets.
  • Use virtual machine extensions.

Module 9: PaaS Compute Options

In this module, you will learn how to administer serverless computing features like Azure App Service, Azure Container Instances, and Kubernetes.

Lessons

  • Azure App Service Plans
  • Azure App Service
  • Container Services
  • Azure Kubernetes Service

Lab: Implement Web Apps

Lab: Implement Azure Kubernetes Service

Lab: Implement Azure Container Instances

After completing this module, students will be able to:

  • Create an app service plan.
  • Create a web app.
  • Implement Azure Container Instances.
  • Implement Azure Kubernetes Service.

Module 10: Data Protection

In this module, you will learn about backing up files and folders, and virtual machine backups.

Lessons

  • File and Folder Backups
  • Virtual Machine Backups

Lab: Implement Data Protection

After completing this module, students will be able to:

  • Backup and restore file and folders.
  • Backup and restore virtual machines.

Module 11: Monitoring

In this module, you will learn about monitoring your Azure infrastructure including Azure Monitor, alerting, and log analytics.

Lessons

  • Azure Monitor
  • Azure Alerts
  • Log Analytics

Lab: Implement Monitoring

After completing this module, students will be able to:

  • Use Azure Monitor.
  • Create Azure alerts.
  • Query using Log Analytics.

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Who should attend this Microsoft Azure training course?

This course is for Azure Administrators. The Azure Administrator implements, manages, and monitors identity, governance, storage, compute, and virtual networks in a cloud environment. The Azure Administrator will provision, size, monitor, and adjust resources as appropriate.

  • Job role: Administrator
  • Preparation for exam: AZ-104

Microsoft Azure Prerequisites

Successful Azure Administrators start this role with experience in virtualization, networking, identity, and storage. Also having knowledge within virtual hard disks. virtual private networks (VPNs), firewalls, and encryption technologies & Control.

Microsoft Azure Administrator MAZ104 Course Overview

This course teaches IT Professionals how to manage their Azure subscriptions, secure identities, administer the infrastructure, configure virtual networking, connect Azure and on-premises sites, manage network traffic, implement storage solutions, create, and scale virtual machines, implement web apps and containers, back up and share data, and monitor your solution.

 

 

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What's included in this Microsoft Azure training course?

  • Experienced Tutor
  • Labs

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accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (4 days)

Online Self-paced (32 hours)

Microsoft Azure IoT Developer AZ220 Course Outline

Within this Microsoft training course, you will learn the following modules:

Module 1: Introduction to IoT and Azure IoT Services

In this module, students will begin by examining the business considerations for various IoT implementations and reviewing how the Azure IoT Reference Architecture supports IoT solutions. This module also provides students with an overview of the Azure services commonly used in an IoT solution and introduces the Azure portal.

Lessons

  • Introduction to IoT Solution Architecture
  • IoT Hardware and Cloud Services
  • Lab Scenarios for this Course

Lab: Getting Started with Azure

Lab: Setting Started with Azure IoT Services

After completing this module, students will be able to:

  • Explain how IoT and Azure IoT could be applied to their business
  • Describe the core components of an Azure IoT Solution Architecture
  • Describe the Azure IoT Services and how they relate to an IoT solution
  • Create an Azure account and use the Azure portal to create an IoT Hub and DPS service

Module 2: Devices and Device Communication

In this module, students will take a closer look at the Azure IoT Hub service and will learn how to configure secure two-way communication between IoT hub and devices. Students will also be introduced to IoT Hub features such as Device Twins and IoT Hub Endpoints that will be explored in more depth as the course continues.

Lessons

  • IoT Hub Concepts
  • IoT Device Lifecycle Concepts
  • IoT Developer Tools
  • Device Configuration and Communication

Lab: Connect IoT Device to Azure

Lab: Setup the Development Environment

After completing this module, students will be able to:

  • Explain the core features of the IoT Hub services
  • Describe the lifecycle of an Azure IoT device
  • Describe how IoT Hub manages device identities and implements other security features
  • Register devices with the IoT Hub using the Azure portal, Azure CLI, and Visual Studio Code
  • Implement the IoT Hub Device and Service SDKs

Module 3: Device Provisioning at Scale

In this module, students will focus on device provisioning and how to configure and manage the Azure Device Provisioning Service. Students will learn about the enrollment process, auto provisioning and re-provisioning, disenrollment, and how to implement various attestation mechanisms.

Lessons

  • Device Provisioning Service Terms and Concepts
  • Configure and Manage the Device Provisioning Service
  • Device Provisioning Tasks

Lab: Individual Enrollment of Devices in DPS

Lab: Automatic Enrollment of Devices in DPS

After completing this module, students will be able to:

  • Explain the process of device provisioning and the features of the Device Provisioning Service
  • Explain the security considerations associated with device provisioning and how they are managed
  • Implement the Device Provisioning Service SDKs
  • Manage the device enrollment process, including deprovisioning and disenrollment

Module 4: Message Processing and Analytics

In this module, students will examine how IoT Hub and other Azure services can be used to process messages. Students will begin with an investigation of how to configure message and event routing and how to implement routing to built-in and custom endpoints. Students will learn about some of the Azure storage options that are common for IoT solutions. To round out his module, students will implement Azure Stream Analytics and queries for a number of ASA patterns.

Lessons

  • Messages and Message Processing
  • Additional Considerations for IoT Hub Messaging
  • Data Storage and the Lambda Architecture
  • Azure Functions and Stream Analytics

Lab: Device Message Routing

After completing this module, students will be able to:

  • Configure message and event routing
  • Route data to the built-in and custom endpoints
  • Implement message enrichment
  • Implement Azure Stream Analytics Inputs, Queries, and Outputs
  • Store message data in a warm storage for historical purposes and additional analysis
  • Use an Azure Function within a message processing and analytics solution

Module 5: Insights and Business Integration

In this module, students will learn about the Azure services and other Microsoft tools that can be used to generate business insights and enable business integration. Students will implement Azure Logic Apps and Event Grid, and they will configure the connection and data transformations for data visualization tools such as Time Series Insights and Power BI.

Lessons

  • Business Integration for IoT Solutions
  • Data Visualization with Time Series Insights
  • Data Visualization with Power BI

Lab: Integrate IoT Hub with Event Grid

Lab: Explore and Analyze Time Stamped Data with Time Series Insights

After completing this module, students will be able to:

  • Explain the options for business integration within an IoT solution and how to achieve them
  • Develop business integration support using Logic Apps and Event Grid
  • Configure IoT Data for Visualization in Time Series Insights
  • Describe Data Visualization with Power BI

Module 6: Azure IoT Edge Deployment Process

In this module, students will learn how to deploy a module to an Azure IoT Edge device. Students will also learn how to configure and use an IoT Edge device as a gateway device.

Lessons

  • Introduction to Azure IoT Edge
  • Edge Deployment Process
  • Edge Gateway Devices

Lab: Implement an IoT Edge gateway

Lab: Introduction to IoT Edge Deployments

After completing this module, students will be able to:

  • Describe the difference between an IoT device and an IoT Edge device
  • Configure an IoT Edge device
  • Implement an IoT Edge deployment using a deployment manifest
  • Configure an IoT Edge device as a gateway device

Module 7: Azure IoT Edge Modules and Containers

In this module, students will develop and deploy custom edge modules, and will implement support for an offline scenario that relies on local storage. Students will use Visual Studio Code to build custom modules as containers using a supported container engine.

Lessons

  • Develop Custom Edge Modules
  • Offline and Local Storage

Lab: Create and Deploy a Custom Edge Module

Lab: Implement Restricted Network and Offline Scenarios for IoT Edge

After completing this module, students will be able to:

  • Explain the requirements for building a custom edge module
  • Configure Visual Studio Code for developing containerized modules
  • Deploy a custom module to an IoT Edge device
  • Implement local storage on an IoT Edge device in support of an offline scenario

Module 8: Device Management

In this module, students will learn how to implement device management for their IoT solution. Students will develop device management solutions that use devoice twins and solutions that use direct methods.

Lessons

  • Introduction to IoT Device Management
  • Manage IoT and IoT Edge Devices
  • Device Management at Scale

Lab: Implement Automatic Device Management

Lab: Manage Devices using Device Twins and Direct Methods

After completing this module, students will be able to:

  • Describe the most common device management patterns and configuration best practices
  • Describe when and how to use device twins and direct methods to implement device management
  • Implement device management for various patterns using device twins and direct methods
  • Implement device management at scale using automatic device management and jobs

Module 9: Solution Testing, Diagnostics, and Logging

In this module, students will configure logging and diagnostic tools that help developers to test their IoT solution. Students will use IoT Hub and Azure Monitor to configure alerts and track conditions such as device connection state that can be used to troubleshoot issues.

Lessons

  • Monitoring and Logging
  • Troubleshooting

Lab: Configure IoT Hub Monitoring

After completing this module, students will be able to:

  • Describe the options for monitoring and logging an Azure IoT solution
  • Configure Azure Monitor to support of an IoT solution
  • Configure IoT Hub Metrics to support of an IoT solution
  • Implement diagnostics logging
  • Troubleshoot IoT device connection and communication issues

Module 10: Microsoft Defender for IoT and IoT Security Considerations

In this module, students will examine the security considerations that apply to an IoT solution. Students will begin by investigating security as it applies to the solution architecture and best practices, and then look at how Microsoft Defender for IoT supports device deployment and IoT Hub integration. Students then use Microsoft Defender for IoT Agents to enhance the security of their solution.

Lessons

  • Security Fundamentals for IoT Solutions
  • Introduction to Microsoft Defender for IoT
  • Enhance Protection with Microsoft Defender for IoT Agents

Lab: Implementing Microsoft Defender for IoT

After completing this module, students will be able to:

  • Describe security concerns and best practices for an IoT solution
  • Describe the Azure IoT Security Architecture and Threat Modeling
  • Describe the features and support provided by Microsoft Defender for IoT
  • Configure Security Agents and Security Module Twins
  • Aggregate Microsoft Defender for IoT Events

Module 11: Develop with Azure Digital Twins

In this module, students will examine the concepts of an Azure Digital Twins solution and take their first steps toward implementing Azure Digital Twins. Students will begin by investigating the concepts behind the Azure Digital Twins service and an Azure Digital Twins solution, followed by an introduction to the development tools that can be used to build and monitor an Azure Digital Twins solution. Students will then use the development tools to create custom models, build and query an Azure Digital Twins environment graph, ingest IoT device telemetry, and implement business logic and data processing.

Lessons

  • Introduction to Azure Digital Twins
  • Introduction to ADT solution development
  • Monitor and troubleshoot ADT

Lab: Develop Azure Digital Twins solutions

After completing this module, students will be able to:

  • Describe the components of an Azure Digital Twins solution
  • Explain how to create and configure an Azure Digital Twins instance
  • Explain how to create, query, and manage the Azure Digital Twins graph
  • Explain how to ingest Azure Digital data from IoT hub and implement support for downstream services
  • Describe how to monitor and troubleshoot Azure Digital Twins

Module 12: Build an IoT Solution with IoT Central

In this module, students will learn how configure and implement Azure IoT Central as a SaaS solution for IoT. Students will begin with a high-level investigation of IoT Central and how it works. With a basic understanding of IoT central establish, students will move on to creating and managing device templates, and then managing devices in their IoT Central application.

Lessons

  • Introduction to IoT Central
  • Create and Manage Device Templates
  • Manage Devices in Azure IoT Central
  • Business Integration and Data Analysis

After completing this module, students will be able to:

  • Describe the difference between Azure IoT Central and the Azure IoT PaaS services
  • Describe the features provided by Azure IoT Central
  • Describe the purpose and components of a Device Template
  • Create and publish a Device Template
  • Manage devices using rules and notifications
  • Mange devices at scale using jobs

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Prerequisites

To attend this Microsoft Azure IoT Developer training course delegates should hold a basic understanding of PaaS, SaaS, and IaaS implementations. We also recommend Microsoft Azure Fundamentals (AZ-900), or equivalent skills.

Audience

This course is intended for everyone who wants to gain a piece of in-depth knowledge on Microsoft Azure IoT Developer.

Microsoft Azure IoT Developer AZ220 Course Overview

Microsoft Azure is a set of cloud services developed by Microsoft, which allows a developer to build, manage, and deploy applications as well as services on a huge network, using numerous frameworks and tools. Azure supports multiple programming languages such as Java, Node Js, and C#. IoT developer mainly focuses on devolving software, which can allow products to function and connect with other devices. Holding comprehensive knowledge and skills of Microsoft Azure IoT Development will help individuals to get their desired job post as well as for more career advancement.

This 4-days Microsoft Azure IoT Developer training course is aimed to provide delegates with the full understanding of the core Azure IoT services such as Azure Stream Analytics, IoT Hub, time series insights, device provisioning services, etc. During this training course, delegates will be taught about device provisioning at scale, processing and analytics of messages, business integration and insights, Azure IoT edge deployment process, device management of IoT, and more. They will also work on various labs to gain in-depth practical knowledge and skills.

After completing this course, delegates will be able to:

  • Create an Azure account to create a DPS service and IoT Hub using Azure portal
  • Describe Azure IoT device lifecycle
  • Device provisioning tasks
  • Implement the device provisioning service SDKs
  • Aggregate Azure security center for IoT events
  • Manage devices at scale using jobs, and more.

Attaining this course will enable delegates to master proficiency which includes creating, configuring, and managing Azure IoT hub, provision devices using DPS and IoT Hub, implementing message processing, and more. It will make them expert for dealing with real-time organisational tasks.

The Knowledge Academy’s Microsoft Azure IoT Developer training course demonstrates the delegates all the required skills for developing software to allow products to function and connect with other devices.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

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accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (4 days)

Online Self-paced (32 hours)

Designing Microsoft Azure Infrastructure Solutions AZ305 Course Outline

Within this Microsoft training course, you will learn the following modules:

Module 1: Design governance and compute solutions

In this module you will learn about governance and compute solutions.

  • Lessons

  • Design a governance solution
  • Design a compute solution

Lab: Case studies

After completing this module, students will be able to:

  • Design a governance solution.
  • Design a compute solution.

Module 2: Design storage and data integration solutions

In this module, you will learn about non-relational storage, relational storage, and data integration solutions.

Lessons

  • Design a non-relational storage solution
  • Design a relational storage solution
  • Design a data integration solution

Lab: Case studies

After completing this module, students will be able to:

  • Design a non-relational storage solution.
  • Design a relational storage solution.
  • Design a data integration solution.

Module 3: Design app architecture, access, and monitoring solutions

In this module you will learn about app architecture, authentication and authorization, and logging and monitoring solutions.

Lessons

  • Design an app architecture solution
  • Design authentication and authorization solutions
  • Design a logging and monitoring solution

Lab: Case studies

After completing this module, students will be able to:

  • Design an app architecture solution.
  • Design authentication and authorization solutions.
  • Design a logging and monitoring solution.

Module 4: Design network, continuity, and migration solutions

In this module you will learn about networking, business continuity, and migration solutions.

Lessons

  • Design a network infrastructure solution
  • Design a business continuity solution
  • Design a migration solution

Lab: Case studies

After completing this module, students will be able to:

  • Design a networking infrastructure solution.
  • Design a business continuity solution.
  • Design a migration solution.

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Who should attend this Microsoft training course?

Successful students have experience and knowledge in IT operations, including networking, virtualization, identity, security, business continuity, disaster recovery, data platforms, and governance. Students also have experience designing and architecting solutions.

  • Job role: Solution Architect
  • Preparation for exam: AZ-305

Prerequisites

Before attending this course, students must have previous experience deploying or administering Azure resources and strong conceptual knowledge of:

  • Azure Active Directory.
  • Azure compute technologies such as VMs, containers and serverless solutions.
  • Azure virtual networking to include load balancers.
  • Azure Storage technologies (unstructured and databases).
  • General application design concepts such as messaging and high availability.

Designing Microsoft Azure Infrastructure Solutions AZ305 Course Overview

This course teaches Azure Solution Architects how to design infrastructure solutions. Course topics cover governance, compute, application architecture, storage, data integration, authentication, networks, business continuity, and migrations. The course combines lecture with case studies to demonstrate basic architect design principles.

What will you gain from taking this Microsoft training course:

  • Design a governance solution.
  • Design a compute solution.
  • Design an application architecture.
  • Design storage, non-relational and relational.
  • Design data integration solutions.
  • Design authentication, authorization, and identity solutions.
  • Design network solutions.
  • Design backup and disaster recovery solutions.
  • Design monitoring solutions.
  • Design migration solutions.

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What's included in this Microsoft training course?

  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor
  • Labs

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accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (3 days)

Online Self-paced (24 hours)

Designing and Implementing Microsoft Azure Networking Solutions AZ700​ Training Course Outline

Module 1: Introduction to Azure Virtual Networks

  • Explore Azure Virtual Networks
  • Configure Public IP Services
  • Design Name Resolution for Your Virtual Network
  • Enable Cross-VNet Connectivity with Peering
  • Implement Virtual Network Traffic Routing
  • Configure Internet Access with Azure Virtual NAT

Lab: Exercise: Design and Implement a Virtual Network in Azure

Lab: Exercise: Configure DNS Settings in Azure

Lab: Exercise: Connect Two Azure Virtual Networks Using Global Virtual Network Peering

Module 2: Design and Implement Hybrid Networking

  • Design and Implement Azure VPN Gateway
  • Connect Networks with Site-to-site VPN Connections
  • Connect Devices to Networks with Point-to-Site VPN Connections
  • Connect Remote Resources by Using Azure Virtual WANs
  • Create a Network Virtual Appliance (NVA) in a Virtual Hub

Lab: Exercise: Create a Virtual WAN by Using Azure Portal

Lab: Exercise: Create and Configure a Virtual Network Gateway

Module 3: Design and Implement Azure ExpressRoute

  • Explore Azure ExpressRoute
  • Design an ExpressRoute Deployment
  • Configure Peering for an ExpressRoute Deployment
  • Connect an ExpressRoute Circuit to a VNet
  • Connect Geographically Dispersed Networks with ExpressRoute Global Reach
  • Improve Data Path Performance Between Networks with ExpressRoute FastPath
  • Troubleshoot ExpressRoute Connection Issues

Lab: Exercise: Configure an ExpressRoute Gateway

Lab: Exercise: Provision an ExpressRoute Circuit

Module 4: Load Balancing Non-HTTP(S) Traffic in Azure

  • Explore Load Balancing
  • Design and Implement Azure Load Balancer Using the Azure Portal
  • Explore Azure Traffic Manager

Lab: Exercise: Create a Traffic Manager Profile Using the Azure portal

Lab: Exercise: Create and Configure an Azure Load Balancer

Module 5: Load Balancing HTTP(S) Traffic in Azure

  • Design Azure Application Gateway
  • Configure Azure Application Gateway
  • Design and Configure Azure Front Door

Lab: Exercise: Deploy Azure Application Gateway

Lab: Exercise: Create a Front Door for a Highly Available Web Application

Module 6: Design and Implement Network Security

  • Secure Your Virtual Networks in the Azure Portal
  • Deploy Azure DDoS Protection by Using the Azure Portal
  • Deploy Network Security Groups by Using the Azure Portal
  • Design and Implement Azure Firewall
  • Working with Azure Firewall Manager
  • Implement a Web Application Firewall on Azure Front Door

Lab: Exercise: Deploy and Configure Azure Firewall Using the Azure Portal

Lab: Exercise: Secure Your Virtual Hub Using Azure Firewall Manager

Lab: Exercise: Configure DDoS Protection on a Virtual Network Using the Azure Portal

Module 7: Design and Implement Private Access to Azure Services

  • Define Private Link Service and Private Endpoint
  • Explain Virtual Network Service Endpoints
  • Integrate Private Link with DNS
  • Integrate Your App Service with Azure Virtual Networks

Lab: Exercise: Create an Azure Private Endpoint Using Azure Powershell

Lab: Exercise: Restrict Network Access to PaaS Resources with Virtual Network Service Endpoints

Module 8: Design and Implement Network Monitoring

  • Monitor Your Networks with Azure Monitor
  • Monitor Your Networks with Azure Network Watcher

Lab: Exercise: Monitor a load Balancer Resource by Using Azure Monitor

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Prerequisites

To attend this Designing and Implementing Microsoft Azure Networking Solutions AZ700 Training course, delegates should have:

  • Understanding of on-premises virtualisation technologies such as VMs, virtual networking, and virtual hard disks.
  • Understanding of network configurations like TCP/IP, Domain Name System (DNS), Virtual Private Networks (VPNs), firewalls, and encryption technologies.
  • Understanding of software-defined networking and hybrid network connectivity methods such as VPN.
  • Understanding resilience and disaster recovery, including high availability and restore operations.
  • Understanding required to configure and manage virtual networks.

Audience

This Designing and Implementing Microsoft Azure Networking Solutions AZ700 Training is ideal for anyone who wants to gain knowledge of Azure networking solutions. However, this will be more beneficial for Network Engineers.

Designing and Implementing Microsoft Azure Networking Solutions AZ700​ Training Course Overview

Azure networking services offer a wide range of networking features combined or independently can be used. Azure gives the scalability, performance, high availability, and enterprise-grade security needed to handle the most demanding workloads. It helps organisations by delivering consistent and low-latency computing to their clients via services that integrate smoothly across on-premises, multi-cloud, and edge locations. Studying Designing and Implementing Microsoft Azure Networking Solutions AZ700 Training course will help learners to design, implement, and maintain Azure networking solutions effectively. This training will help learners expand their skills and undertake a variety of tremendous job opportunities in various international companies.

This 3-day Designing and Implementing Microsoft Azure Networking Solutions AZ700 Training course covers all the essential topics by which delegates will become familiar with Azure networking solutions. During this training, they will learn about how to connect geographically dispersed networks with ExpressRoute global reach. They will also learn about how to configure peering for an ExpressRoute deployment, configure Azure application gateway, connect remote resources by using Azure virtual WANs, implement virtual network traffic routing, explore Azure traffic manager, and many more. Our highly professional trainer with years of experience in teaching Microsoft courses will conduct this training and help delegates get a comprehensive understanding of designing and implementing Microsoft Azure networking solutions.

Other than the above topics, delegates will also learn the following concepts:

  • Explore load balancing
  • Design and implement Azure VPN gateway
  • Configure public IP services
  • Explore Azure ExpressRoute
  • Create a Network Virtual Appliance (NVA) in a virtual hub

After attending the Designing and Implementing Microsoft Azure Networking Solutions AZ700 Training course, delegates will be able to design and configure the Azure application gateway. They will also be able to implement a Web Application Firewall (WAF) on the Azure front door.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

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accredited by

Our Microsoft Certifications (Microsoft Partner) course is accredited by Microsoft

Online Instructor-led (3 days)

Online Self-paced (24 hours)

Troubleshooting Microsoft Azure Connectivity AZ720 Certification Course Outline

Module 1: Troubleshoot Business Continuity Issues

  • Troubleshoot Backup Issues
  • Troubleshoot Recovery Issues

Module 2: Troubleshoot Hybrid and Cloud Connectivity Issues

  • Troubleshoot Virtual Network Connectivity
  • Troubleshoot Name Resolution Issues
  • Troubleshoot Point-to-Site Virtual Private Network Connectivity
  • Troubleshoot Site-to-Site Virtual Private Network Connectivity
  • Troubleshoot Azure ExpressRoute Connectivity Issues

Module 3: Troubleshoot Platform as a Service Issues

  • Troubleshoot PaaS Services
  • Troubleshoot PaaS Integration Issues

Module 4: Troubleshoot Authentication and Access Control Issues

  • Troubleshoot Azure AD Authentication
  • Troubleshoot Hybrid Authentication
  • Troubleshoot Authorisation Issues

Module 5: Troubleshoot Networks

  • Troubleshoot Azure Network Security Issues
  • Troubleshoot Azure Network Security Groups
  • Troubleshoot Azure Firewall Issues
  • Troubleshoot Latency Issues
  • Troubleshoot Routing and Traffic Control
  • Troubleshoot Load-Balancing Issues

Module 6: Troubleshoot VM Connectivity Issues

  • Troubleshoot Azure Bastion
  • Troubleshoot Just-In-Time VM Access

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Prerequisites 

There are no formal prerequisites for attending this course. However, knowledge of networking, hybrid connections, and network security will be beneficial.

Audience

This Troubleshooting Microsoft Azure Connectivity AZ720 Training Course is ideal for anyone who wants to gain knowledge of Azure Connectivity. However, this will be more beneficial for:

  • Azure Administrators
  • Support Engineers

Troubleshooting Microsoft Azure Connectivity AZ720 Certification Course Overview

Microsoft Azure is a collection of cloud computing services that includes remotely hosted and managed versions of proprietary Microsoft technologies as well as open technologies such as various Linux distributions that may be deployed inside a virtual machine. It offers a variety of cloud services such as compute, analytics, storage, and networking. This training assists learners to successfully troubleshoot Microsoft Azure connectivity. It provides an isolated environment for your applications, allows you to simply control traffic from resources, has a highly secure network, high network connectivity, and easily develops advanced network topologies. Pursuing this training equips learners with the necessary abilities and approaches that will ultimately improve their employment chances and income.

In this 3-day Troubleshooting Microsoft Azure Connectivity AZ720 Training Course, delegates will gain an in-depth knowledge of Troubleshooting Microsoft Azure Connectivity. During this training, delegates will learn about how to troubleshoot virtual network connectivity, name resolution issues, and point-to-site virtual private network connectivity. They will also learn how to troubleshoot backup issues and recovery issues. Our highly professional trainer with years of experience in teaching such courses will conduct this training course and will help you get a complete understanding of this course.

Course Objectives:

  • To verify the connection to the Azure target IP addresses
  • To restore data that has been backed up using Microsoft Azure Recovery services
  • To troubleshoot virtual WAN issues in Microsoft Azure
  • To connect to an application running on an Azure virtual machine.
  • To avoid sign-in problems with Conditional Access

At the end of this training, delegates will be able to use available tools to analyse issues related to hybrid environments, business continuity, Platform as a Service, Infrastructure as a Service, networking, virtual machine connectivity, and access control.

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  • Delegate pack consisting of course notes and exercises
  • Courseware
  • Experienced Instructor

Show moredown

accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (4 days)

Online Self-paced (32 hours)

Data Engineering on Microsoft Azure DP203 Course Outline

Within this Microsoft training course, you will learn the following modules:

Module 1: Explore compute and storage options for data engineering workloads

This module provides an overview of the Azure compute and storage technology options that are available to data engineers building analytical workloads. This module teaches ways to structure the data lake, and to optimize the files for exploration, streaming, and batch workloads. The student will learn how to organize the data lake into levels of data refinement as they transform files through batch and stream processing. Then they will learn how to create indexes on their datasets, such as CSV, JSON, and Parquet files, and use them for potential query and workload acceleration.

Lessons

  • Introduction to Azure Synapse Analytics
  • Describe Azure Databricks
  • Introduction to Azure Data Lake storage
  • Describe Delta Lake architecture
  • Work with data streams by using Azure Stream Analytics

Lab: Explore compute and storage options for data engineering workloads

  • Combine streaming and batch processing with a single pipeline
  • Organize the data lake into levels of file transformation
  • Index data lake storage for query and workload acceleration

After completing this module, students will be able to:

  • Describe Azure Synapse Analytics
  • Describe Azure Databricks
  • Describe Azure Data Lake storage
  • Describe Delta Lake architecture
  • Describe Azure Stream Analytics

Module 2: Run interactive queries using Azure Synapse Analytics serverless SQL pools

In this module, students will learn how to work with files stored in the data lake and external file sources, through T-SQL statements executed by a serverless SQL pool in Azure Synapse Analytics. Students will query Parquet files stored in a data lake, as well as CSV files stored in an external data store. Next, they will create Azure Active Directory security groups and enforce access to files in the data lake through Role-Based Access Control (RBAC) and Access Control Lists (ACLs).

Lessons

  • Explore Azure Synapse serverless SQL pools capabilities
  • Query data in the lake using Azure Synapse serverless SQL pools
  • Create metadata objects in Azure Synapse serverless SQL pools
  • Secure data and manage users in Azure Synapse serverless SQL pools

Lab: Run interactive queries using serverless SQL pools

  • Query Parquet data with serverless SQL pools
  • Create external tables for Parquet and CSV files
  • Create views with serverless SQL pools
  • Secure access to data in a data lake when using serverless SQL pools
  • Configure data lake security using Role-Based Access Control (RBAC) and Access Control List

After completing this module, students will be able to:

  • Understand Azure Synapse serverless SQL pools capabilities
  • Query data in the lake using Azure Synapse serverless SQL pools
  • Create metadata objects in Azure Synapse serverless SQL pools
  • Secure data and manage users in Azure Synapse serverless SQL pools

Module 3: Data exploration and transformation in Azure Databricks

This module teaches how to use various Apache Spark DataFrame methods to explore and transform data in Azure Databricks. The student will learn how to perform standard DataFrame methods to explore and transform data. They will also learn how to perform more advanced tasks, such as removing duplicate data, manipulate date/time values, rename columns, and aggregate data.

Lessons

  • Describe Azure Databricks
  • Read and write data in Azure Databricks
  • Work with DataFrames in Azure Databricks
  • Work with DataFrames advanced methods in Azure Databricks

Lab: Data Exploration and Transformation in Azure Databricks

  • Use DataFrames in Azure Databricks to explore and filter data
  • Cache a DataFrame for faster subsequent queries
  • Remove duplicate data
  • Manipulate date/time values
  • Remove and rename DataFrame columns
  • Aggregate data stored in a DataFrame

After completing this module, students will be able to:

  • Describe Azure Databricks
  • Read and write data in Azure Databricks
  • Work with DataFrames in Azure Databricks
  • Work with DataFrames advanced methods in Azure Databricks

Module 4: Explore, transform, and load data into the Data Warehouse using Apache Spark

This module teaches how to explore data stored in a data lake, transform the data, and load data into a relational data store. The student will explore Parquet and JSON files and use techniques to query and transform JSON files with hierarchical structures. Then the student will use Apache Spark to load data into the data warehouse and join Parquet data in the data lake with data in the dedicated SQL pool.

Lessons

  • Understand big data engineering with Apache Spark in Azure Synapse Analytics
  • Ingest data with Apache Spark notebooks in Azure Synapse Analytics
  • Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics
  • Integrate SQL and Apache Spark pools in Azure Synapse Analytics

Lab: Explore, transform, and load data into the Data Warehouse using Apache Spark

  • Perform Data Exploration in Synapse Studio
  • Ingest data with Spark notebooks in Azure Synapse Analytics
  • Transform data with DataFrames in Spark pools in Azure Synapse Analytics
  • Integrate SQL and Spark pools in Azure Synapse Analytics

After completing this module, students will be able to:

  • Describe big data engineering with Apache Spark in Azure Synapse Analytics
  • Ingest data with Apache Spark notebooks in Azure Synapse Analytics
  • Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics
  • Integrate SQL and Apache Spark pools in Azure Synapse Analytics

Module 5: Ingest and load data into the data warehouse

This module teaches students how to ingest data into the data warehouse through T-SQL scripts and Synapse Analytics integration pipelines. The student will learn how to load data into Synapse dedicated SQL pools with PolyBase and COPY using T-SQL. The student will also learn how to use workload management along with a Copy activity in a Azure Synapse pipeline for petabyte-scale data ingestion.

Lessons

  • Use data loading best practices in Azure Synapse Analytics
  • Petabyte-scale ingestion with Azure Data Factory

Lab: Ingest and load Data into the Data Warehouse

  • Perform petabyte-scale ingestion with Azure Synapse Pipelines
  • Import data with PolyBase and COPY using T-SQL
  • Use data loading best practices in Azure Synapse Analytics

After completing this module, students will be able to:

  • Use data loading best practices in Azure Synapse Analytics
  • Petabyte-scale ingestion with Azure Data Factory

Module 6: Transform data with Azure Data Factory or Azure Synapse Pipelines

This module teaches students how to build data integration pipelines to ingest from multiple data sources, transform data using mapping data flowss, and perform data movement into one or more data sinks.

Lessons

  • Data integration with Azure Data Factory or Azure Synapse Pipelines
  • Code-free transformation at scale with Azure Data Factory or Azure Synapse Pipelines

Lab: Transform Data with Azure Data Factory or Azure Synapse Pipelines

  • Execute code-free transformations at scale with Azure Synapse Pipelines
  • Create data pipeline to import poorly formatted CSV files
  • Create Mapping Data Flows

After completing this module, students will be able to:

  • Perform data integration with Azure Data Factory

  • Perform code-free transformation at scale with Azure Data Factory

Module 7: Orchestrate data movement and transformation in Azure Synapse Pipelines

In this module, you will learn how to create linked services, and orchestrate data movement and transformation using notebooks in Azure Synapse Pipelines.

Lessons

  • Orchestrate data movement and transformation in Azure Data Factory

Lab: Orchestrate data movement and transformation in Azure Synapse Pipelines

  • Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines

After completing this module, students will be able to:

  • Orchestrate data movement and transformation in Azure Synapse Pipelines

Module 8: End-to-end security with Azure Synapse Analytics

In this module, students will learn how to secure a Synapse Analytics workspace and its supporting infrastructure. The student will observe the SQL Active Directory Admin, manage IP firewall rules, manage secrets with Azure Key Vault and access those secrets through a Key Vault linked service and pipeline activities. The student will understand how to implement column-level security, row-level security, and dynamic data masking when using dedicated SQL pools.

Lessons

  • Secure a data warehouse in Azure Synapse Analytics
  • Configure and manage secrets in Azure Key Vault
  • Implement compliance controls for sensitive data

Lab: End-to-end security with Azure Synapse Analytics

  • Secure Azure Synapse Analytics supporting infrastructure
  • Secure the Azure Synapse Analytics workspace and managed services
  • Secure Azure Synapse Analytics workspace data

After completing this module, students will be able to:

  • Secure a data warehouse in Azure Synapse Analytics
  • Configure and manage secrets in Azure Key Vault
  • Implement compliance controls for sensitive data

In this module, students will learn how Azure Synapse Link enables seamless connectivity of an Azure Cosmos DB account to a Synapse workspace. The student will understand how to enable and configure Synapse link, then how to query the Azure Cosmos DB analytical store using Apache Spark and SQL serverless.

Lessons

  • Design hybrid transactional and analytical processing using Azure Synapse Analytics
  • Configure Azure Synapse Link with Azure Cosmos DB
  • Query Azure Cosmos DB with Apache Spark pools
  • Query Azure Cosmos DB with serverless SQL pools
  • Configure Azure Synapse Link with Azure Cosmos DB
  • Query Azure Cosmos DB with Apache Spark for Synapse Analytics
  • Query Azure Cosmos DB with serverless SQL pool for Azure Synapse Analytics

After completing this module, students will be able to:

  • Design hybrid transactional and analytical processing using Azure Synapse Analytics
  • Configure Azure Synapse Link with Azure Cosmos DB
  • Query Azure Cosmos DB with Apache Spark for Azure Synapse Analytics
  • Query Azure Cosmos DB with SQL serverless for Azure Synapse Analytics

Module 10: Real-time Stream Processing with Stream Analytics

In this module, students will learn how to process streaming data with Azure Stream Analytics. The student will ingest vehicle telemetry data into Event Hubs, then process that data in real time, using various windowing functions in Azure Stream Analytics. They will output the data to Azure Synapse Analytics. Finally, the student will learn how to scale the Stream Analytics job to increase throughput.

Lessons

  • Enable reliable messaging for Big Data applications using Azure Event Hubs
  • Work with data streams by using Azure Stream Analytics
  • Ingest data streams with Azure Stream Analytics

Lab: Real-time Stream Processing with Stream Analytics

  • Use Stream Analytics to process real-time data from Event Hubs
  • Use Stream Analytics windowing functions to build aggregates and output to Synapse Analytics
  • Scale the Azure Stream Analytics job to increase throughput through partitioning
  • Repartition the stream input to optimize parallelization

After completing this module, students will be able to:

  • Enable reliable messaging for Big Data applications using Azure Event Hubs
  • Work with data streams by using Azure Stream Analytics
  • Ingest data streams with Azure Stream Analytics

Module 11: Create a Stream Processing Solution with Event Hubs and Azure Databricks

In this module, students will learn how to ingest and process streaming data at scale with Event Hubs and Spark Structured Streaming in Azure Databricks. The student will learn the key features and uses of Structured Streaming. The student will implement sliding windows to aggregate over chunks of data and apply watermarking to remove stale data. Finally, the student will connect to Event Hubs to read and write streams.

Lessons

  • Process streaming data with Azure Databricks structured streaming

Lab: Create a Stream Processing Solution with Event Hubs and Azure Databricks

  • Explore key features and uses of Structured Streaming
  • Stream data from a file and write it out to a distributed file system
  • Use sliding windows to aggregate over chunks of data rather than all data
  • Apply watermarking to remove stale data
  • Connect to Event Hubs read and write streams

After completing this module, students will be able to:

  • Process streaming data with Azure Databricks structured streaming

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Who should attend this Microsoft training course?

The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course data analysts and data scientists who work with analytical solutions built on Microsoft Azure.

  • Job role: Data Engineer
  • Preparation for exam: DP-203

Prerequisites

Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions. 

Specifically completing:

  • AZ-900 - Azure Fundamentals.
  • DP-900 - Microsoft Azure Data Fundamentals.

Data Engineering on Microsoft Azure DP203 Course Overview

In this course, the student will learn about the data engineering as it pertains to working with batch and real-time analytical solutions using Azure data platform technologies. Students will begin by understanding the core compute and storage technologies that are used to build an analytical solution. The students will learn how to interactively explore data stored in files in a data lake. They will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines. The students will also learn the various ways they can transform the data using the same technologies that is used to ingest data. They will understand the importance of implementing security to ensure that the data is protected at rest or in transit. The student will then show how to create a real-time analytical system to create real-time analytical solutions.

What you will gain from taking this Microsoft training course:

  • Explore compute and storage options for data engineering workloads in Azure.
  • Run interactive queries using serverless SQL pools.
  • Perform data Exploration and Transformation in Azure Databricks.
  • Explore, transform, and load data into the Data Warehouse using Apache Spark.
  • Ingest and load Data into the Data Warehouse.
  • Transform Data with Azure Data Factory or Azure Synapse Pipelines.
  • Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines.
  • Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link.
  • Perform end-to-end security with Azure Synapse Analytics.
  • Perform real-time Stream Processing with Stream Analytics.
  • Create a Stream Processing Solution with Event Hubs and Azure Databricks.

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What's included within this Microsoft training course?

  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor
  • Labs

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accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (4 days)

Online Self-paced (32 hours)

DP-300: Administering Microsoft Azure SQL Solutions

Administering Microsoft Azure SQL Solutions DP300 Course Outline

Within this Microsoft Azure training course, you will learn the following modules:

Module 1: Introduction to Azure Database Administration

This module explores the role of a database administrator in the world of Azure SQL. It also provides some foundational information relevant to the overall content. This includes a review of the various SQL Server-based options (SQL Server in a VM, SQL Managed Instance, and Azure SQL Database).

Lessons

  • Prepare to maintain SQL databases on Azure

After completing this module, students will be able to:

  • Understand the role of Azure Database Administrator as it fits in with other data platform roles
  • Be able to describe the key differences between the SQL Server-based database options
  • Describe other features for Azure SQL platforms available

Module 2: Plan and Implement Data Platform Resources

This module introduces methods for deploying data platform resources in Azure SQL. You will learn about options for both upgrading and migrating existing SQL databases to Azure. You will learn how to set up Azure resources to host SQL Server on a Virtual Machine, a SQL Managed Instance, and SQL Database. You will learn how to determine which options are best based on specific requirements including the High Availability and Disaster Recovery (HADR) needs. They will learn to calculate resource requirements and understand hybrid approaches.

Lessons

  • Deploy IaaS solutions with Azure SQL
  • Deploy PaaS solutions with Azure SQL
  • Evaluate strategies for migrating to Azure SQL
  • Migrate SQL workloads to Azure SQL Databases
  • Migrate SQL workloads to Azure Managed Instances

Lab: Provision SQL Server on an Azure Virtual Machine

  • Explore the Azure Portal
  • Deploy a SQL Server on an Azure Virtual Machine
  • Connect to SQL Server on an Azure Virtual Machine

Lab: Provision an Azure SQL Database

  • Create a Virtual Network
  • Deploy an Azure SQL Database
  • Connect to an Azure SQL Database using Azure Data Studio
  • Query an Azure SQL Database using SQL Notebook

After completing this module, students will be able to:

  • Explore the basics of SQL Server in an Infrastructure as a Service (IaaS) offering
  • Understand PaaS provisioning and deployment options
  • Evaluate migration scenarios to SQL Managed Instance and SQL Database
  • Evaluate and implement a strategy for moving a database to Azure

Module 3: Implement a Secure Environment for a Database Service

This module explores the practices of securing your SQL Server Database as well as an Azure SQL database. This includes a review of the various SQL Server-based options as well as the various Azure options for securing Azure SQL Database. Students will lean why security is crucial when working with databases and explain authentication options for Azure SQL Database.

Lessons

  • Configure database authentication and authorization
  • Protect data in-transit and at rest
  • Implement compliance controls for sensitive data

Lab: Configure a server-based firewall rule using the Azure portal

  • Configure Azure SQL Database firewall rules
  • Validate access

Lab: Authorize Access to Azure SQL Database with Azure Active Directory

  • Create users
  • Manage access to database objects
  • Validate access

Lab: Enable Microsoft Defender for SQL and Data Classification

  • Enable Microsoft Defender for Azure SQL Database
  • Configure Data Classification for Azure SQL Database

After completing this module, students will be able to:

  • Understand the differences between Windows, SQL Server, and Azure Active Directory Authentication
  • Describe and configure both data-at-rest encryption solutions as well as data-in-transit encryption
  • Implement a data sensitivity solution

Module 4: Monitor and Optimize Operational Resources

This module will teach you about resource optimization for your databases created using either IaaS or PaaS services. The module also covers monitoring server and hardware resources. It will familiarize you with the various tools available for monitoring performance and establishing a baseline. You will learn how to interpret performance metrics for the most critical resources. You will also learn how to troubleshoot database performance using Azure SQL Insights.

Lessons

  • Describe performance monitoring
  • Configure SQL Server resources for optimal performance
  • Configure databases for optimal performance

Lab: Isolate performance problems through monitoring

  • Review CPU utilization in Azure portal
  • Identify high CPU queries

Lab: Detect and correct fragmentation issues

  • Investigate index fragmentation
  • Rebuild fragmented indexes
  • Validate performance improvements

After completing this module, students will be able to:

  • Monitor activity and compare to a baseline
  • Identify major causes of performance problems
  • Configure resources for optimal performance
  • Configure a user database for optimal performance

Module 5: Optimize Query Performance

Query execution plans are potentially the most important aspect of database performance. Improving bad plans is certainly an area where a small amount of effort can bring huge improvements. While hardware issues can limit query performance, improving hardware usually yields performance improvements in the 10-20% range, at most. More commonly database administrators encounter queries that are not optimized, have stale or missing statistics, have missing indexes, or poor database design choices that lead to the database engine doing more work than is necessary to return results for a given query. Improving the plans can sometimes yield performance improvements in the 100-200% range or even more, meaning that after improving a plan with better indexes or statistics, a query could run twice or three times as fast! This module provides details on how to analyze individual query performance and determine where improvements can be made.

Lessons

  • Explore query performance optimization
  • Explore performance-based database design
  • Evaluate performance improvements

Lab: Identify database design issues

  • Examine the query and identify the problem
  • Identify ways to fix the warning message
  • Improve the code

Lab: Identify and resolve blocking issues

  • Run blocked queries report
  • Enable Read Commit Snapshot isolation level
  • Evaluate performance improvements

Lab: Isolate problem areas in poorly performing queries in a SQL Database

  • Generate actual execution plan
  • Resolve a suboptimal query plan
  • Use Query Store to detect and handle regression
  • Examine Top Resource Consuming Queries report
  • Force a better execution plan
  • Use query hints to impact performance

After completing this module, students will be able to:

  • Analyze query plans and identify problem areas
  • Evaluate potential query improvements using Query Store
  • Review table and index design
  • Determine whether query or design changes have had a positive effect

Module 6: Automate database tasks

A common goal for database administrators in many environments is to automate as many of their repetitive tasks. This can be as simple as using scripting to automate a backup process, and as complex as building a fully automated alerting system. This module provides details of automating tasks to simplify the DBA’s job. Methods include scheduling tasks for regular maintenance jobs, as well as how to use elastic jobs and Azure Automation runbooks.

Lessons

  • Automate deployment of database resources
  • Create and manage SQL Agent jobs
  • Manage Azure PaaS tasks using automation

Lab: Deploy an automation runbook to automatically rebuild indexes

  • Create an Automation Account
  • Connect to an existing Azure SQL Database
  • Configure Automation Account assets
  • Create a PowerShell runbook
  • Create a schedule for a runbook

Lab: Deploy Azure SQL Database using an Azure Resource Manager template

  • Explore Azure Resource Manager template

Lab: Create a CPU status alert for a SQL Server

  • Create an alert when a CPU exceeds an average of 80 percent

After completing this module, students will be able to:

  • Deploy resources using automated deployment scripts
  • Create scheduled tasks
  • Create notifications and alerts
  • Configure automation for PaaS services

Module 7: Plan and Implement a High Availability and Disaster Recovery Solution

Data must be available when the business needs it. That means the solutions hosting the data must be designed with availability and recoverability in mind. Suppose you work for a company that sells widgets both in stores and online. Your main application uses a highly transactional database for orders. What would happen if the server or platform hosting the transactional database had a problem that made it unavailable or inaccessible for some reason? What impact would it have on the business? If the right solution is put in place, the database would come online in a reasonable timeframe with minimal effort, thus allowing business to continue with little-to-no impact. This module and its associated lab cover configuring, testing, and managing a solution for high availability and disaster recovery (HADR) in Azure, for both Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) deployments. This module will not only cover basic requirements, but also the various options available to achieve HADR.

Lessons

  • High Availability and Disaster Recovery Strategies
  • IaaS Platform and Database Tools for HADR
  • PaaS Platform and Database Tools for HADR
  • Database Backup and Recovery

Lab: Backup to URL and Restore from URL

  • Create a credential
  • Backup to URL
  • Validate backup through Azure CLI and Storage Explorer
  • Restore from URL

Lab: Configure geo-replication for Azure SQL Database

  • Enable geo-replication
  • Failover to a secondary region

After completing this module, students will be able to:

  • The difference between recovery time and recovery point objectives
  • The available HADR options for both IaaS and PaaS
  • The considerations for planning and configuring HADR solutions including how backup and restore fi
  • The factors that comprise a HADR strategy
  • How to configure a high availability solution via a hands-on lab

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Who should attend this Microsoft Azure training course?

The audience for this course is data professionals managing data and databases who want to learn about administering the data platform technologies that are available on Microsoft Azure. This course is also valuable for data architects and application developers who need to understand what technologies are available for the data platform with Azure and how to work with those technologies through applications.

  • Job role: Database Administrator
  • Preparation for exam: DP-300

Microsoft Azure Prerequisites

Successful Azure Database Administrators start this role with professional experience in database management and technical knowledge of cloud technologies.  

Specifically:

  • Working with, maintaining, and developing with SQL Server.
  • Experience with Azure, such as deploying and managing resources.

Administering Microsoft Azure SQL Solutions DP300 Course Overview.

This course provides students with the knowledge and skills to administer a SQL Server database infrastructure for cloud, on-premises, and hybrid relational databases and who work with the Microsoft PaaS relational database offerings. Additionally, it will be of use to individuals who develop applications that deliver content from SQL-based relational databases.

What will you gain within this Microsoft Azure training course?

  • Plan, deploy and configure Azure SQL offerings.
  • Monitor database performance and tune a database and queries for optimum performance.
  • Plan and configure a High Availability Solution.

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What's included within this Microsoft Azure training course?

  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor
  • Labs

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Exam DP-300: Administering Microsoft Azure SQL Solutions Information

  • Plan and implement data platform resources (20—25%)
  • Implement a secure environment (15—20%)
  • Monitor, configure, and optimize database resources (20—25%)
  • Configure and manage automation of tasks (15—20%)
  • Plan and configure a high availability and disaster recovery (HA/DR) environment (20—25%)

Passing Score: 700

Candidates for this exam should have subject matter expertise in building database solutions that are designed to support multiple workloads built with Azure SQL database services.

Candidates for this exam are database administrators who manage on-premises and cloud databases built with SQL Server and SQL database services.

The Azure database administrator implements and manages the operational aspects of cloud-native and hybrid data platform solutions built on SQL Server and SQL database services. Professionals in this role use a variety of methods and tools to perform and automate day-to-day operations, including applying knowledge of using T-SQL for administrative management purposes.

These professionals are responsible for management, availability, security, and performance monitoring and optimization of database solutions. They evaluate and implement migration strategies for moving databases to Azure. Plus, they work with Azure data engineers, Azure solution architects, Azure developers, and other professionals to manage operational aspects of data platform solutions.

Candidates for this exam should have knowledge of and experience with Azure SQL Edge, Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines (Windows and Linux).

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accredited by

Our Microsoft training course is accredited by Microsoft

Online Instructor-led (4 days)

Online Self-paced (32 hours)

Configuring Windows Server Hybrid Advanced Services AZ801 Course Outline

Within this course you will learn the following modules:

Module 1: Windows Server security

This module discusses how to protect an Active Directory environment by securing user accounts to least privilege and placing them in the Protected Users group. The module covers how to limit authentication scope and remediate potentially insecure accounts. The module also describes how to harden the security configuration of a Windows Server operating system environment. In addition, the module discusses the use of Windows Server Update Services to deploy operating system updates to computers on the network. Finally, the module covers how to secure Windows Server DNS to help protect the network name resolution infrastructure.

Lessons

  • Secure Windows Sever user accounts
  • Hardening Windows Server
  • Windows Server Update Management
  • Secure Windows Server DNS

Lab: Configuring security in Windows Server

  • Configuring Windows Defender Credential Guard
  • Locating problematic accounts
  • Implementing LAPS

After completing this module, students will be able to:

  • Diagnose and remediate potential security vulnerabilities in Windows Server resources.
  • Harden the security configuration of the Windows Server operating system environment.
  • Deploy operating system updates to computers on a network by using Windows Server Update Services.
  • Secure Windows Server DNS to help protect the network name resolution infrastructure.
  • Implement DNS policies.

Module 2: Implementing security solutions in hybrid scenarios

This module describes how to secure on-premises Windows Server resources and Azure IaaS workloads. The module covers how to improve the network security for Windows Server infrastructure as a service (IaaS) VMs and how to diagnose network security issues with those VMs. In addition, the module introduces Azure Security Center and explains how to onboard Windows Server computers to Security Center. The module also describes how to enable Azure Update Management, deploy updates, review an update assessment, and manage updates for Azure VMs. The module explains how Adaptive application controls and BitLocker disk encryption are used to protect Windows Server IaaS VMs. Finally, the module explains how to monitor Windows Server Azure IaaS VMs for changes in files and the registry, as well as monitoring modifications made to application software.

Lessons

  • Implement Windows Server IaaS VM network security.
  • Audit the security of Windows Server IaaS Virtual Machines
  • Manage Azure updates
  • Create and implement application allowlists with adaptive application control
  • Configure BitLocker disk encryption for Windows IaaS Virtual Machines
  • Implement change tracking and file integrity monitoring for Windows Server IaaS VMs

Lab: Using Azure Security Center in hybrid scenarios

  • Provisioning Azure VMs running Windows Server
  • Configuring Azure Security Center
  • Onboarding on-premises Windows Server into Azure Security Center
  • Verifying the hybrid capabilities of Azure Security Center
  • Configuring Windows Server security in Azure VMs

After completing this module, students will be able to:

  • Diagnose network security issues in Windows Server IaaS virtual machines.
  • Onboard Windows Server computers to Azure Security Center.
  • Deploy and manage updates for Azure VMs by enabling Azure Automation Update Management.
  • Implement Adaptive application controls to protect Windows Server IaaS VMs.
  • Configure Azure Disk Encryption for Windows IaaS VMs.
  • Back up and recover encrypted data.
  • Monitor Windows Server Azure IaaS VMs for changes in files and the registry.

Module 3: Implementing high availability

This module describes technologies and options to create a highly available Windows Server environment. The module introduces Clustered Shared Volumes for shared storage access across multiple cluster nodes. The module also highlights failover clustering, stretch clusters, and cluster sets for implementing high availability of Windows Server workloads. The module then discusses high availability provisions for Hyper-V and Windows Server VMs, such as network load balancing, live migration, and storage migration. The module also covers high availability options for shares hosted on Windows Server file servers. Finally, the module describes how to implement scaling for virtual machine scale sets and load balanced VMs, and how to implement Azure Site Recovery.

Lessons

  • Introduction to Cluster Shared Volumes.
  • Implement Windows Server failover clustering.
  • Implement high availability of Windows Server VMs.
  • Implement Windows Server File Server high availability.
  • Implement scale and high availability with Windows Server VMs.

Lab: Implementing failover clustering

  • Configuring iSCSI storage
  • Configuring a failover cluster
  • Deploying and configuring a highly available file server
  • Validating the deployment of the highly available file server

After completing this module, students will be able to:

  • Implement highly available storage volumes by using Clustered Share Volumes.
  • Implement highly available Windows Server workloads using failover clustering.
  • Describe Hyper-V VMs load balancing.
  • Implement Hyper-V VMs live migration and Hyper-V VMs storage migration.
  • Describe Windows Server File Server high availablity options.
  • Implement scaling for virtual machine scale sets and load-balanced VMs.
  • Implement Azure Site Recovery.

Module 4: Disaster recovery in Windows Server

This module introduces Hyper-V Replica as a business continuity and disaster recovery solution for a virtual environment. The module discusses Hyper-V Replica scenarios and use cases, and prerequisites to use it. The module also discusses how to implement Azure Site Recovery in on-premises scenarios to recover from disasters.

Lessons

  • Implement Hyper-V Replica
  • Protect your on-premises infrastructure from disasters with Azure Site Recovery

Lab: Implementing Hyper-V Replica and Windows Server Backup

  • Implementing Hyper-V Replica
  • Implementing backup and restore with Windows Server Backup

After completing this module, students will be able to:

  • Describe Hyper-V Replica, pre-requisites for its use, and its high-level architecture and components
  • Describe Hyper-V Replica use cases and security considerations.
  • Configure Hyper-V Replica settings, health monitoring, and failover options.
  • Describe extended replication.
  • Replicate, failover, and failback virtual machines and physical servers with Azure Site Recovery.

Module 5: Implementing recovery services in hybrid scenarios

This module covers tools and technologies for implementing disaster recovery in hybrid scenarios, whereas the previous module focuses on BCDR solutions for on-premises scenarios. The module begins with Azure Backup as a service to protect files and folders before highlighting how to implement Recovery Vaults and Azure Backup Policies. The module describes how to recover Windows IaaS virtual machines, perform backup and restore of on-premises workloads, and manage Azure VM backups. The module also covers how to provide disaster recovery for Azure infrastructure by managing and orchestrating replication, failover, and failback of Azure virtual machines with Azure Site Recovery.

Lessons

  • Implement hybrid backup and recovery with Windows Server IaaS
  • Protect your Azure infrastructure with Azure Site Recovery
  • Protect your virtual machines by using Azure Backup

Lab: Implementing Azure-based recovery services

  • Implementing the lab environment
  • Creating and configuring an Azure Site Recovery vault
  • Implementing Hyper-V VM protection by using Azure Site Recovery vault
  • Implementing Azure Backup

After completing this module, students will be able to:

  • Recover Windows Server IaaS virtual machines by using Azure Backup.
  • Use Azure Backup to help protect the data for on-premises servers and virtualized workloads.
  • Implement Recovery Vaults and Azure Backup policies.
  • Protect Azure VMs with Azure Site Recovery.
  • Run a disaster recovery drill to validate protection.
  • Failover and failback Azure virtual machines.

Module 6: Upgrade and migrate in Windows Server

This module discusses approaches to migrating and updating Windows Server workloads running in earlier versions of Windows Server. The module covers the necessary strategies needed to move domain controllers to Windows Server 2022 and describes how the Active Directory Migration Tool can consolidate domains within a forest or migrate domains to a new AD DS forest. The module also discusses the use of Storage Migration Service to migrate files and files shares from existing file servers to new servers running Windows Server 2022. Finally, the module covers how to install and use the Windows Server Migration Tools cmdlets to migrate commonly used server roles from earlier versions of Windows Server.

Lessons

  • Active Directory Domain Services migration
  • Migrate file server workloads using Storage Migration Service
  • Migrate Windows Server roles

Lab: Migrating Windows Server workloads to IaaS VMs

  • Deploying AD DS domain controllers in Azure
  • Migrating file server shares by using Storage Migration Service

After completing this module, students will be able to:

  • Compare upgrading an AD DS forest and migrating to a new AD DS forest.
  • Describe the Active Directory Migration Tool (ADMT).
  • Identify the requirements and considerations for using Storage Migration Service.
  • Describe how to migrate a server with storage migration.
  • Use the Windows Server Migration Tools to migrate specific Windows Server roles.

Module 7: Implementing migration in hybrid scenarios

This module discusses approaches to migrating workloads running in Windows Server to an infrastructure as a service (IaaS) virtual machine. The module introduces using Azure Migrate to assess and migrate on-premises Windows Server instances to Microsoft Azure. The module also covers how migrate a workload running in Windows Server to an infrastructure as a service (IaaS) virtual machine (VM) and to Windows Server 2022 by using Windows Server migration tools or the Storage Migration Service. Finally, this module describes how to use the Azure Migrate App Containerization tool to containerize and migrate ASP.NET applications to Azure App Service.

Lessons

  • Migrate on-premises Windows Server instances to Azure IaaS virtual machines
  • Upgrade and migrate Windows Server IaaS virtual machines
  • Containerize and migrate ASP.NET applications to Azure App Service

Lab: Migrating on-premises VMs servers to IaaS VMs

  • Implementing assessment and discovery of Hyper-V VMs using Azure Migrate
  • Implementing migration of Hyper-V workloads using Azure Migrate

After completing this module, students will be able to:

  • Plan a migration strategy and choose the appropriate migration tools.
  • Perform server assessment and discovery using Azure Migrate.
  • Migrate Windows Server workloads to Azure VM workloads using Azure Migrate.
  • Explain how to migrate workloads using Windows Server Migration tools.
  • Migrate file servers by using the Storage Migration Service.
  • Discover and containerize ASP.NET applcations running on Windows.
  • Migrate a containerized application to Azure App Service.

Module 8: Server and performance monitoring in Windows Server

This module introduces a range of tools to monitor the operating system and applications on a Windows Server computer as well as describing how to configure a system to optimize efficiency and to troubleshoot problems. The module covers how Event Viewer provides a convenient and accessible location for observing events that occur, and how to interpret the data in the event log. The module also covers how to audit and diagnose a Windows Server environment for regulatory compliance, user activity, and troubleshooting. Finally, the module explains how to troubleshoot AD DS service failures or degraded performance, including recovery of deleted objects and the AD DS database, and how to troubleshoot hybrid authentication issues.

Lessons

  • Monitor Windows Server performance
  • Manage and monitor Windows Server event logs
  • Implement Windows Server auditing and diagnostics
  • Troubleshoot Active Directory

Lab: Monitoring and troubleshooting Windows Server

  • Establishing a performance baseline
  • Identifying the source of a performance problem
  • Viewing and configuring centralized event logs

After completing this module, students will be able to:

  • Explain the fundamentals of server performance tuning.
  • Use built-in tools in Windows Server to monitor server performance.
  • Use Server Manager and Windows Admin Center to review event logs.
  • Implement custom views.
  • Configure an event subscription.
  • Audit Windows Server events.
  • Configure Windows Server to record diagnostic information.
  • Recover the AD DS database and objects in AD DS.
  • Troubleshoot AD DS replication.
  • Troubleshoot hybrid authentication issues.

Module 9: Implementing operational monitoring in hybrid scenarios

This module covers using monitoring and troubleshooting tools, processes, and best practices to streamline app performance and availability of Windows Server IaaS VMs and hybrid instances. The module describes how to implement Azure Monitor for IaaS VMs in Azure, implement Azure Monitor in on-premises environments, and use dependency maps. The module then explains how to enable diagnostics to get data about a VM, view VM metrics in Azure Metrics Explorer, and create a metric alert to monitor VM performance. The module then covers how to monitor VM performance by using Azure Monitor VM Insights. The module then describes various aspects of troubleshooting on premises and hybrid network connectivity, including how to diagnose common issues with DHCP, name resolution, IP configuration, and routing. Finally, the module examines how to troubleshoot configuration issues that impact connectivity to Azure-hosted Windows Server virtual machines (VMs), as well as approaches to resolve issues with VM startup, extensions, performance, storage, and encryption.

Lessons

  • Monitor Windows Server IaaS Virtual Machines and hybrid instances
  • Monitor the health of your Azure virtual machines by using Azure Metrics Explorer and metric alerts
  • Monitor performance of virtual machines by using Azure Monitor VM Insights
  • Troubleshoot on-premises and hybrid networking
  • Troubleshoot Windows Server Virtual Machines in Azure

Lab: Monitoring and troubleshooting of IaaS VMs running Windows Server

  • Enabling Azure Monitor for virtual machines
  • Setting up a VM with boot diagnostics
  • Setting up a Log Analytics workspace and Azure Monitor VM Insights

After completing this module, students will be able to:

  • Implement Azure Monitor for IaaS VMs in Azure and in on-premises environments.
  • Implement Azure Monitor for IaaS VMs in Azure and in on-premises environments.
  • View VM metrics in Azure Metrics Explorer.
  • Use monitoring data to diagnose problems.
  • Evaluate Azure Monitor Logs and configure Azure Monitor VM Insights.
  • Configure a Log Analytics workspace.
  • Troubleshoot on-premises connectivity and hybrid network connectivity.
  • Troubleshoot AD DS service failures or degraded performance.
  • Recover deleted security objects and the AD DS database.
  • Troubleshoot hybrid authentication issues.

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Audience Profile

This four-day course is intended for Windows Server Hybrid Administrators who have experience working with Windows Server and want to extend the capabilities of their on-premises environments by combining on-premises and hybrid technologies. Windows Server Hybrid Administrators who already implement and manage on-premises core technologies want to secure and protect their environments, migrate virtual and physical workloads to Azure Iaas, enable an available, fully redundant environment, and perform monitoring and troubleshooting.

Job role: Administrator

Prerequisites

Before attending this course, students must have:

  • Experience with managing Windows Server operating system and Windows Server workloads in on-premises scenarios, including AD DS, DNS, DFS, Hyper-V, and File and Storage Services
  • Experience with common Windows Server management tools (implied in the first prerequisite).
  • Basic knowledge of core Microsoft compute, storage, networking, and virtualization technologies (implied in the first prerequisite).
  • Experience and an understanding of core networking technologies such as IP addressing, name resolution, and Dynamic Host Configuration Protocol (DHCP)
  • Experience working with and an understanding of Microsoft Hyper-V and basic server virtualization concepts
  • An awareness of basic security best practices
  • Basic understanding of security-related technologies (firewalls, encryption, multi-factor authentication, SIEM/SOAR).
  • Basic knowledge of on-premises resiliency Windows Server-based compute and storage technologies (Failover Clustering, Storage Spaces).
  • Basic experience with implementing and managing IaaS services in Microsoft Azure
  • Basic knowledge of Azure Active Directory
  • Experience working hands-on with Windows client operating systems such as Windows 10 or Windows 11
  • Basic experience with Windows PowerShell

An understanding of the following concepts as related to Windows Server technologies:

  • High availability and disaster recovery
  • Automation
  • Monitoring
  • Troubleshooting

Configuring Windows Server Hybrid Advanced Services AZ801 Course Overview

his course teaches IT Professionals to configure advanced Windows Server services using on-premises, hybrid, and cloud technologies. The course teaches IT Professionals how to leverage the hybrid capabilities of Azure, how to migrate virtual and physical server workloads to Azure IaaS, and how to secure Azure VMs running Windows Server. The course also teaches IT Professionals how to perform tasks related to high availability, troubleshooting, and disaster recovery. The course highlights administrative tools and technologies including Windows Admin Center, PowerShell, Azure Arc, Azure Automation Update Management, Microsoft Defender for Identity, Azure Security Center, Azure Migrate, and Azure Monitor.

What will you gain from this training course?

  • Harden the security configuration of the Windows Server operating system environment.
  • Enhance hybrid security using Azure Security Center, Azure Sentinel, and Windows Update Management.
  • Apply security features to protect critical resources.
  • Implement high availability and disaster recovery solutions.
  • Implement recovery services in hybrid scenarios.
  • Plan and implement hybrid and cloud-only migration, backup, and recovery scenarios.
  • Perform upgrades and migration related to AD DS, and storage.
  • Manage and monitor hybrid scenarios using WAC, Azure Arc, Azure Automation and Azure Monitor.
  • Implement service monitoring and performance monitoring and apply troubleshooting.

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What's Included in this training course:

  • Experienced Instructor
  • Labs

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Microsoft Azure Training FAQs

FAQ's

Microsoft Azure is a cloud computing platform the development and deployment of mobile and PC applications.
Our classroom Microsoft courses include a courseware book, refreshments, and a certificate upon completion. Where appropriate, they also include exams.
Our Azure training courses are available across the world in thousands of locations, making it easy to find a course near you.
Prerequisites for our Azure courses vary, please see the courses themselves for details.
The Knowledge Academy is the Leading global training provider in the world for Microsoft Azure Training.
The price for Microsoft Azure Training certification in Canada starts from CAD.

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Many delivery methods

Flexible delivery methods are available depending on your learning style.

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High quality resources

Resources are included for a comprehensive learning experience.

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"Really good course and well organised. Trainer was great with a sense of humour - his experience allowed a free flowing course, structured to help you gain as much information & relevant experience whilst helping prepare you for the exam"

Joshua Davies, Thames Water

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