MLOps Automation and Model Monitoring 5 Sections22 LessonsLifetime Access
Curriculum
- 5 Sections
- 22 Lessons
- Lifetime Access
Expand all sectionsCollapse all sections
- ML Workflow Automation (CI/CD Pipelines) with AWS4 Items
- ML Solution Monitoring and Maintenance with AWS15 Items
- 2.1Exploring the Features of Responsible AI
- 2.2Understanding the Legal Risks of Generative AI
- 2.3Using Tools for Responsible ML: SageMaker Clarify and SageMaker Model Monitor
- 2.4Monitoring Model/Data Quality and Bias Drift with SageMaker Clarify [Hands-On]
- 2.5Monitoring Production Models with SageMaker Model Monitor [Hands-On]
- 2.6Introducing SageMaker Model Cards
- 2.7Creating SageMaker Model Cards [Hands-On]
- 2.8Troubleshooting Latency and Performance Issues with X-Ray and CloudWatch [Hands-On]
- 2.9Setting Up CloudTrail Trails [Hands-On]
- 2.10Setting Up Dashboards to Monitor Performance Metrics with QuickSight [Hands-On]
- 2.11Setting Up Dashboards to Monitor Performance Metrics with CloudWatch [Hands-On]
- 2.12Monitoring Infrastructure Using EventBridge Events [Hands-On]
- 2.13Using SageMaker Inference Recommender [Hands-On]
- 2.14Monitoring Costs Using Cost Explorer, Trusted Advisor and AWS Budgets [Hands-On]
- 2.15Reducing Costs with Purchasing Options: Spot, On-Demand and Savings Plan [Hands-On]
- Resources1 Item
- Practice Lab1 Item
- Claim Your Certificate1 Item
Using AWS CodePipeline [Hands-On]
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