Domains Distribution

• Design and implement an MLOps infrastructure: 38
• Implement machine learning model lifecycle and operations: 59
• Design and implement a GenAIOps infrastructure: 49
• Implement generative AI quality assurance and observability: 27
• Optimize generative AI systems and model performance: 27

Training Materials

Exam guide

• https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ai-300

MSLearn Courses

• https://learn.microsoft.com/en-us/training/modules/automated-evaluation-genaiops/
• https://learn.microsoft.com/en-us/training/modules/deploy-model-github-actions/
• https://learn.microsoft.com/en-us/training/modules/evaluate-optimize-agents/
• https://learn.microsoft.com/en-us/training/modules/experiment-azure-machine-learning/
• https://learn.microsoft.com/en-us/training/modules/monitor-generative-ai-app/
• https://learn.microsoft.com/en-us/training/modules/perform-hyperparameter-tuning-azure-machine-learning-pipelines/
• https://learn.microsoft.com/en-us/training/modules/plan-prepare-genaiops/
• https://learn.microsoft.com/en-us/training/modules/prompt-versioning-genaiops/
• https://learn.microsoft.com/en-us/training/modules/run-pipelines-azure-machine-learning/
• https://learn.microsoft.com/en-us/training/modules/tracing-generative-ai-app/
• https://learn.microsoft.com/en-us/training/modules/trigger-azure-machine-learn-jobs-github-actions/
• https://learn.microsoft.com/en-us/training/modules/trigger-github-actions-trunk-based-development/
• https://learn.microsoft.com/en-us/training/modules/work-environments-github-actions/
• https://learn.microsoft.com/en-us/training/paths/build-first-machine-operations-workflow/
• https://learn.microsoft.com/en-us/training/paths/operationalize-gen-ai-apps/