AI-300T00
AI-300T00: Operationalize machine learning and generative AI solutions
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4 Days
Prerequisites
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.
What you’ll learn in 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 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.
Course Outline
• 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
• 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
Further information
If you would like to know more about this course please contact us
