Microsoft AI-300T00 - Operationalise Machine Learning and Generative AI Solutions

Length 4 days

Course overview

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Why study this course

This course prepares learners to design, implement, and operate Machine Learning Operations (MLOps) and Generative AI Operations (GenAIOps) solutions on Azure. It covers building secure and scalable AI infrastructure, managing the full lifecycle of traditional machine learning models with Azure Machine Learning, and deploying, evaluating, monitoring, and optimising generative AI applications and agents using Microsoft Foundry. Learners will gain hands-on knowledge of automation, continuous integration and delivery, infrastructure as code, and observability by using tools such as GitHub Actions, Azure CLI, and Bicep. The course emphasises collaboration with data science and DevOps teams to deliver reliable, production-ready AI systems aligned with modern MLOps and GenAIOps best practices.

Please note: This course is due to be released by Microsoft on March 20th, 2026.

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What you’ll learn

After completing this course, students will be able to:

Operationalise machine learning models and generative AI applications
Explore data, and run experiments
Train and deploy models
Optimise language models for AI applications

Microsoft Azure at Lumify Work

As part of Lumify Group, Lumify Work has skilled more people in Microsoft technologies than any other organisation in Australia and New Zealand. We have a campus in the Philippines, too. We offer the broadest range of instructor-led training courses, from end user to architect level. We are proud to be the winner of the Microsoft MCT Superstars Award for FY24, which formally recognises us as having the highest quality Microsoft Certified Trainers in ANZ.

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Who is the course for?

This course is intended for data scientists, machine learning engineers, and DevOps professionals who want to design and operate production-grade AI solutions on Azure. It is suited for learners with experience in Python, a foundational understanding of machine learning concepts, and basic familiarity with DevOps practices such as source control, CI/CD, and command-line tools, who are preparing to implement MLOps and GenAIOps workflows using Azure-native services.

Course subjects

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

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

Prerequisites

Prerequisites

Programming experience with Python or R
Experience developing and training machine learning models
Familiarity with basic Azure Machine Learning concepts
Familiar with fundamental generative AI concepts and services in Azure

Microsoft - Training Solutions Partner - Microsoft Certified Trainers - MCT Superstars Award FY24

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Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.