Curriculum
5 Sections
14 Lessons
24 Hours
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Design and Implement an MLOps Infrastructure (15–20%)
3 Items
1.1
Machine Learning workspace resources
1.2
Workspace assets
1.3
Infrastructure as code for ML
Model Life Cycle and Operations (25–30%)
4 Items
2.1
Orchestrate model training
2.2
Model registration and versioning
2.3
Deploy models to production
2.4
Monitor and maintain models
Design and Implement a GenAIOps Infrastructure (20–25%)
3 Items
3.1
Foundry environments
3.2
Deploy and manage foundation models
3.3
Prompt versioning with source control
Generative AI Quality Assurance and Observability (10–15%)
2 Items
4.1
Evaluation and validation
4.2
Observability for apps and agents
Optimize Generative AI Systems (10–15%)
2 Items
5.1
Optimize RAG
5.2
Fine-tuning and customization
Machine Learning Operations Engineer Associate (AI-300)
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