AI-300T00: Operationalize machine learning and generative AI solutions

Course Overview

This four day, instructor led AI-300T00: Operationalize Machine Learning and Generative AI Solutions teaches AI engineers, data scientists, and DevOps professionals how to build, deploy, and manage scalable AI solutions on Microsoft Azure. The course covers MLOps and GenAIOps practices including model experimentation, automated training, CI/CD pipelines, deployment, monitoring, optimization, and AI application management in production environments. At the completion of this course, participants will be able to:

• Implement MLOps workflows using Azure Machine Learning
• Automate model training, experimentation, and hyperparameter tuning
• Build and manage machine learning pipelines
• Use GitHub Actions to enable CI/CD automation for AI solutions
• Deploy, monitor, and manage machine learning and generative AI applications
• Evaluate, optimize, and debug AI systems using GenAIOps practices and tracing tools

Schedule

Program Level

Associate

Training Delivery Methods

VILT+ILT

Duration

4 Days / 32 Hour Training

Course Outline

Module 1: Operationalize Machine Learning Models (MLOps)

• Experiment with Azure Machine Learning
• Perform Hyperparameter Tuning with Azure Machine Learning
• Run Pipelines in Azure Machine Learning
• Trigger Azure Machine Learning Jobs with GitHub Actions
• Trigger GitHub Actions with Feature-Based Development
• Work with Environments in GitHub Actions
• Deploy a Model with GitHub Actions

Module 2: Operationalize Generative AI Applications (GenAIOps)

• Plan and Prepare a GenAIOps Solution
• Manage Prompts for Agents in Microsoft Foundry with GitHub
• Evaluate and Optimize AI Agents Through Structured Experiments
• Automate AI Evaluations with Microsoft Foundry and GitHub Actions
• Monitor Your Generative AI Application
• Analyze and Debug Your Generative AI App with Tracing

Exam Information