Operationalize Machine Learning and Generative AI Solutions AI300 Course Overview

Course syllabus

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Operationalize Machine Learning and Generative AI Solutions AI300 Course Outline

Module 1: Experiment with Azure Machine Learning

  • Introduction
  • Preprocess Data and Configure Featurization
  • Run an Automated Machine Learning Experiment
  • Evaluate and Compare Models
  • Configure MLflow for Model Tracking in Notebooks
  • Train and Track Models in Notebooks
  • Evaluate Models with the Responsible AI Dashboard
  • Exercise - Find the Best Classification Model with Azure Machine Learning

Module 2: Perform Hyperparameter Tuning with Azure Machine Learning

  • Introduction
  • Define a Search Space
  • Configure a Sampling Method
  • Configure Early Termination
  • Use a Sweep Job for Hyperparameter Tuning
  • Exercise - Run a Sweep Job

Module 3: Run Pipelines in Azure Machine Learning

  • Introduction
  • Create Components 
  • Create a Pipeline
  • Run a Pipeline Job
  • Exercise - Run a Pipeline Job

Module 4: Trigger Azure Machine Learning Jobs with GitHub Actions

  • Introduction
  • Understand the Business Problem 
  • Explore the Solution Architecture 
  • Use GitHub Actions for Model Training
  • Exercise

Module 5: Trigger GitHub Actions with Feature-Based Development

  • Introduction
  • Understand the Business Problem
  • Explore the Solution Architecture
  • Trigger a Workflow
  • Exercise

Module 6: Work with Environments in GitHub Actions

  • Introduction
  • Understand the Business Problem
  • Explore the Solution Architecture
  • Set up Environments
  • Exercise

Module 7: Deploy a Model with GitHub Actions

  • Introduction
  • Understand the Business Problem
  • Explore the Solution Architecture
  • Model Deployment
  • Exercise

Module 8: Plan and Prepare a GenAIOps Solution

  • Introduction
  • Explore Use Cases for GenAIOps
  • Select the Right Generative AI Model
  • Understand the Development Lifecycle of a Language Model Application
  • Explore Available Tools and Frameworks to Implement GenAIOps
  • Exercise - Compare Language Models from the Model Catalog

Module 9: Manage Prompts for Agents in Microsoft Foundry with GitHub

  • Introduction
  • Apply Version Control to Prompts
  • Understand Microsoft Foundry Agents and Prompt Versioning
  • Organize Prompts in GitHub repositories
  • Develop Safe Prompt Deployment Workflows
  • Exercise - Develop Prompt and Agent Versions

Module 10: Evaluate and Optimize AI Agents through Structured Experiments

  • Introduction
  • Design Evaluation Experiments
  • Apply Git-based Workflows to Optimization Experiments
  • Apply Evaluation Rubrics for Consistent Scoring
  • Exercise - Evaluate and Compare AI Agent Versions

Module 11: Automate AI Evaluations with Microsoft Foundry and GitHub Actions

  • Introduction
  • Understand why Automated Evaluations Matter
  • Align Evaluators with Human Criteria
  • Create Evaluation Datasets
  • Implement Batch Evaluations with Python
  • Integrate Evaluations into GitHub Actions
  • Exercise - Set up Automated Evaluations

Module 12: Monitor your Generative AI Application

  • Introduction
  • Why Do you Need to Monitor?
  • Understand Key Metrics to Monitor
  • Explore How to Monitor with Azure
  • Integrate Monitoring into your App
  • Interpret Monitoring Results
  • Exercise - Enable Monitoring for a Generative AI Application

Module 13: Analyze and Debug your Generative AI App with Tracing

  • Introduction
  • Why Do you Need to Use Tracing?
  • Identify what to Trace in Generative AI Applications
  • Implement Tracing in Generative AI Applications
  • Debug Complex Workflows with Advanced Tracing Patterns
  • Make Informed Decisions with Trace Data Analysis
  • Exercise - Enable Tracing for a Generative AI Application
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Who Should Attend this Operationalize Machine Learning and Generative AI Solutions AI300 Course?

The Operationalise Machine Learning and Generative AI Solutions AI300 Course is designed for professionals who want to build practical skills in Machine Learning operationalisation, GenAIOps, AI deployment, and workflow automation using Microsoft Azure technologies. Here are some professionals who can particularly benefit from attending this course:

  • Machine Learning Engineers
  • AI Engineers
  • Data Scientists
  • Azure AI Developers
  • DevOps Engineers
  • Cloud Solution Architects
  • Automation Professionals

Prerequisites of the Operationalize Machine Learning and Generative AI Solutions AI300 Course

There are no formal prerequisites for attending this Operationalise Machine Learning and Generative AI Solutions AI300 Course. However, a basic understanding of Machine Learning concepts, cloud computing, GitHub workflows, and Microsoft Azure services can be beneficial for delegates.

Operationalize Machine Learning and Generative AI Solutions AI300 Course Overview   

Operationalise Machine Learning and Generative AI Solutions: AI300 Training explores how to automate, deploy, monitor, and optimise Machine Learning and Generative AI workflows using Azure Machine Learning, Microsoft Foundry, and GitHub Actions. 

This training helps delegates develop practical skills in AI workflow automation, hyperparameter tuning, model deployment, GenAIOps, prompt management, AI monitoring, and tracing. Delegates enhance their ability to manage scalable and enterprise-ready AI solutions. 

This 4-Day course offered by The Knowledge Academy helps delegates operationalise AI and Machine Learning solutions using Microsoft Azure technologies. Delegates gain hands-on experience in AI deployment workflows, monitoring, and implementing scalable AI. 

Operationalize Machine Learning and Generative AI Solutions AI300 Course Objectives

  • To understand Machine Learning operationalisation and GenAIOps concepts
  • To learn how to automate AI workflows using Azure Machine Learning and GitHub Actions
  • To develop practical skills in model deployment, monitoring, and optimisation
  • To manage prompts, AI evaluations, and workflow automation using Microsoft Foundry
  • To implement tracing and monitoring techniques for Generative AI applications
  • To understand scalable AI operational practices using Microsoft Azure technologies

Upon completing this Operationalise Machine Learning and Generative AI Solutions AI300 Training, delegates will gain practical knowledge of operationalising AI and Machine Learning solutions using Azure technologies. They will be able to automate workflows, manage AI deployments, and optimise Generative AI applications confidently in real-world environments.

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What’s Included in this Operationalize Machine Learning and Generative AI Solutions AI300 Course?

  • World-Class Training Sessions from Experienced Instructors
  • Interactive Learning with 24*7 Support
  • Digital Delegate Pack

You’ll also get access to the MyTKA Training Portal, which will be your go to hub for all your training.
Hands-On Labs: Included as part of our online instructor-led delivery, these labs provide real-world exercises in a simulated environment guided by expert instructors to enhance your practical skills.
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Looking for Operationalize Machine Learning and Generative AI Solutions AI300 Course in-house or onsite training in Austria? We specialise in corporate group training and bulk bookings for organisations of all sizes in Austria. Our trainers deliver tailored sessions at your premises, online, or hybrid, with best price guarantee, group discounts and flexible scheduling to train your team.

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Learn Operationalize Machine Learning and Generative AI Solutions AI300 Course through The Knowledge Academy’s Online Self-Paced Learning. This flexible and structured format supports your training goals and enables every professional to build skills with confidence.

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Experience the most sought-after learning style with The Knowledge Academy's Operationalize Machine Learning and Generative AI Solutions AI300 Course. Available in 490+ locations across 190+ countries, our hand-picked Classroom venues offer an invaluable human touch. Immerse yourself in a comprehensive, interactive experience with our expert-led Operationalize Machine Learning and Generative AI Solutions AI300 Course sessions.

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Package deals for Operationalize Machine Learning and Generative AI Solutions AI300 Course

Our training experts have compiled a range of course packages on a variety of categories in Operationalize Machine Learning and Generative AI Solutions AI300 Course in Austria, to boost your career. The packages consist of the best possible qualifications with Operationalize Machine Learning and Generative AI Solutions AI300 Course, and allows you to purchase multiple courses at a discounted rate.

Operationalize Machine Learning and Generative AI Solutions AI300 Course FAQs

What is the Operationalise Machine Learning and Generative AI Solutions AI300 Course?

This course teaches delegates how to operationalise Machine Learning and Generative AI solutions using Azure technologies. It covers AI deployment, monitoring, automation, and workflow management. Delegates also learn GenAIOps and AI optimisation practices.

Who should attend this AI300 Course?

This course is ideal for AI Engineers, Machine Learning Engineers, Developers, and DevOps Professionals. It also benefits Cloud Architects and Data Scientists working with AI solutions. Anyone interested in AI operationalisation can attend.

What skills will I gain from this course?

Delegates will learn AI workflow automation, model deployment, monitoring, and prompt management. They will gain practical experience with Azure Machine Learning and GitHub Actions. The course also covers tracing and AI evaluation techniques.

Does this course include practical exercises?

Yes, this course includes multiple hands-on exercises and practical labs. Delegates will work on AI pipelines, deployment workflows, evaluations, and monitoring tasks. These exercises help reinforce real-world operational AI skills.

What technologies are covered in this training?

This training covers Azure Machine Learning, Microsoft Foundry, GitHub Actions, MLflow, and GenAIOps workflows. It also includes AI tracing, prompt versioning, and AI monitoring tools. Delegates learn enterprise AI operational practices.

Will I learn about GenAIOps in this course?

Yes, GenAIOps is an important part of this course. Delegates learn how to operationalise Generative AI applications and manage AI workflows effectively. The course also explains prompt management and AI evaluation automation.

Does the course cover AI monitoring and tracing?

Yes, delegates learn how to monitor and trace Generative AI applications using Azure tools. The course explains key monitoring metrics and tracing workflows. Delegates also learn how to analyse AI performance data effectively.

Is programming knowledge required for this course?

Basic programming knowledge can be helpful for understanding AI workflows and automation tasks. Familiarity with Python and GitHub is beneficial. However, the course supports learners with different technical backgrounds.

Why choose The Knowledge Academy in Austria over others?

The Knowledge Academy stands out as a prestigious training provider known for its extensive course offerings, expert instructors, adaptable learning formats, and industry recognition. It's a dependable option for those seeking this certification.

What is the cost/training fees for Operationalize Machine Learning and Generative AI Solutions AI300 Course in Austria?

The training fees for Operationalize Machine Learning and Generative AI Solutions AI300 Course in Austria starts from €5495

Which is the best training institute/provider of Operationalize Machine Learning and Generative AI Solutions AI300 Course in Austria?

The Knowledge Academy is one of the Leading global training provider for Operationalize Machine Learning and Generative AI Solutions AI300 Course.

What are the best Microsoft Azure Certification courses in Austria?

Please see our Microsoft Azure Certification courses available in Austria

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