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AWS SageMaker: training, deploying and monitoring models on AWS

How to run a real machine learning project on AWS SageMaker, from data on S3 to a monitored endpoint, with the invoice in view at every step.

Course Duration: 7h

What You'll Learn

  • Position SageMaker's components against the ML lifecycle you already know
  • Configure Studio, notebooks and IAM with just enough privilege
  • Store data on S3 in a shape SageMaker training jobs can consume
  • Launch training jobs with a built-in container, then with your own script
  • Tune hyperparameters and deploy real-time, serverless or batch inference
  • Automate the whole flow with SageMaker Pipelines and the Model Registry
  • Watch data drift with Model Monitor and cap the invoice with budgets

Prerequisites

  • Course 20 (MLOps): experiment tracking, model registry, monitoring
  • Working knowledge of AWS S3 and IAM
  • Python, pandas, scikit-learn and XGBoost basics

Course Modules

  1. Overview of SageMaker and its components
  2. Studio, notebooks and working environments
  3. Data on S3 and the Feature Store
  4. Training jobs and built-in containers
  5. Custom containers and training scripts
  6. Automatic hyperparameter tuning
  7. Real-time and serverless endpoints
  8. Batch transform for large volumes
  9. SageMaker Pipelines and the Model Registry
  10. Monitoring, alerts and cost control

The running example

The churn model from course 20 is ported to SageMaker, one module at a time. Data lands on S3 in module 3, XGBoost trains on it in module 4, a custom scikit-learn script replaces it in module 5, tuning refines it in module 6, endpoints serve it in modules 7 and 8, a pipeline orchestrates everything in module 9, and Model Monitor plus a budget close the loop in module 10. Every module prints the estimated cost of what you launched.

Assessment and certificate

The course ends with a 40-question exam covering every module. On success, a certificate of completion is issued; its number is verifiable on the platform.

Free courses, by contrast, end with a 5-question quiz and a preview of the certificate, without certification.