Microsoft Certified: MLOps Engineer Associate (AI-300)

On this accelerated Microsoft Certified: MLOps Engineer Associate (AI-300) course, you’ll gain an understanding of how to design, implement, and operate Machine Learning Operations (MLOps) and Generative AI Operations (GenAIOps) solutions on Azure.

The course 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 optimizing 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 emphasizes collaboration with data science and DevOps teams to deliver reliable, production-ready AI systems aligned with modern MLOps and GenAIOps best practices.

Through Firebrand’s Lecture | Lab | Review method, you’ll get certified faster than traditional training and access official courseware, learn from certified instructors, and train in a distraction-free environment.

Audience

This course is ideal for:

• Data Scientists, Machine Learning Engineers, and DevOps professionals who want to design and operate production-grade AI solutions on Azure
• 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

• Module 1: Experiment with Azure Machine Learning
• Module 2: Perform hyperparameter tuning with Azure Machine Learning
• Module 3: Run pipelines in Azure Machine Learning
• Module 4: Trigger Azure Machine Learning jobs with GitHub Actions
• Module 5: Trigger GitHub Actions with feature-based development
• Module 6: Work with environments in GitHub Actions
• Module 7: Deploy a model with GitHub Actions

Learning Path 2: Operationalize generative AI applications (GenAIOps)

• Module 1: Plan and prepare a GenAIOps solution
• Module 2: Manage prompts for agents in Microsoft Foundry with GitHub
• Module 3: Evaluate and optimize AI agents through structured experiments
• Module 4: Automate AI evaluations with Microsoft Foundry and GitHub Actions
• Module 5: Monitor your generative AI application
• Module 6: Analyze and debug your generative AI app with tracing

Before attending this accelerated course, you should have:

• Programming experience with Python or R Experience developing and training machine learning models
• Familiarity with basic Azure Machine Learning concepts
• Familiarity with fundamental generative AI concepts and services in Azure
• Consider completing the Microsoft Azure AI Fundamentals: Generative AI learning path first

At the end of this accelerated course, you’ll sit the official Microsoft Certified: MLOps Engineer Associate (AI-300) exam.