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In this course, you will learn to accelerate the process to prepare, build, train, deploy, and monitor ML solutions using Amazon SageMaker Studio.
Amazon SageMaker Studio helps data scientists prepare, build, train, deploy, and monitor machine learning (ML) models quickly. It does this by bringing together a broad set of capabilities purpose-built for ML. This course prepares experienced data scientists to use the tools that are a part of SageMaker Studio, including Amazon CodeWhisperer and Amazon CodeGuru Security scan extensions, to improve productivity at every step of the ML lifecycle.
JupyterLab Extensions in SageMaker Studio
Demonstration: SageMaker user interface demo
Using SageMaker Data Wrangler for data processing
Hands-On Lab: Analyze and prepare data using Amazon SageMaker Data Wrangler
Using Amazon EMR
Using AWS Glue interactive sessions
Using SageMaker Processing with custom scripts
SageMaker training jobs
Built-in algorithms
Bring your own script
Bring your own container
SageMaker Experiments
SageMaker Debugger
SageMaker Jumpstart
Hands-On Lab: Analyzing, Detecting, and Setting Alerts Using SageMaker Debugger
Automatic model tuning
SageMaker Autopilot: Automated ML
Demonstration: SageMaker Autopilot
Bias detection
SageMaker Model Registry
SageMaker Pipelines
SageMaker model inference options
Scaling
Testing strategies, performance, and optimization
Amazon SageMaker Model Monitor
Discussion: Case study
Demonstration: Model Monitoring
Accrued cost and shutting down
Updates
Challenge 1: Analyze and prepare the dataset with SageMaker Data Wrangler
Challenge 2: Create feature groups in SageMaker Feature Store
Challenge 3: Perform and manage model training and tuning using SageMaker Experiments
(Optional) Challenge 4: Use SageMaker Debugger for training performance and model optimization
Challenge 5: Evaluate the model for bias using SageMaker Clarify
Challenge 6: Perform batch predictions using model endpoint
(Optional) Challenge 7: Automate full model development process using SageMaker Pipeline
We recommend that all attendees of this course have: