Operationalize Machine Learning And Generative AI Solutions AI300 Course - Czech Republic

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

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.

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.