1. Introduction to SageMaker
2. Setting Up Your SageMaker Studio Development Environment
3. Training Models on Amazon SageMaker
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3.1 Introduction to Model Training in SageMaker (4:56)
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3.2 Training an XGBoost model using Built-in Algorithms (15:57)
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3.3 Training a scikit-learn model using Pre-built Docker Images and Custom Code (12:39)
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3.4 Installing Custom python Requirements (7:25)
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3.5 Preprocessing Data with SageMaker Preprocessor (8:28)
4. Experiment Management on SageMaker
5. Deploying Models on Amazon SageMaker
6. Model Monitoring
7. Conclusion
