Amazon SageMaker Studio for Data Scientists course material links

Please not that this is not a prep course for any AWS certification!

This document contains links mentioned in the “Amazon SageMaker Studio for Data Scientists” course.

Module 0: Course Overview

Full name: Amazon SageMaker Studio for Data Scientists

Product code: 300-MLASMS-13

These links are based on the course version 1.3.20.

Online and classroom course options: Amazon SageMaker Studio for Data Scientists

The official course material: eVantage Bookshelf (VitalSource)

Additional material: Skill Builder

AWS Service Documents:

• Overviews
• Technical

Module 1: Amazon SageMaker Studio Setup

Websites

• Amazon SageMaker
• Use Amazon SageMaker Notebooks
• Compare Amazon SageMaker Notebooks
• Where you can create a notebook job
• Amazon Elastic File System (EFS)
• Add External Git Repositories to SageMaker Studio Notebooks
• Dive Deep into Amazon SageMaker Studio Notebook Architecture
• Customize Amazon SageMaker Studio Using Lifecycle Configurations
• Collaboration with shared spaces
• Share ML Models and Notebooks with SageMaker JumpStart
• Customizations - SageMaker Studio Admin Guide
• 10 Jupyter Lab Extensions to Boost Your Productivity
• Amazon Q - Generative AI Assistant
• Accelerate your Software Development Lifecycle with Amazon Q
• Q Language IDE Support
• Onboard to Amazon SageMaker Quick Start
• Automate a Centralized Deployment of Amazon SageMaker Studio with AWS Service Catalog
• Granting SageMaker Studio Permissions Required to Use Projects
• Create SageMaker Projects with Image Building CI/CD Pipelines
• SageMaker JumpStart pretrained models
• IAM Best Practices – Grant Least Privilege
• Configuring SageMaker Studio for Teams with Resource Isolation

AWS Services

• Amazon SageMaker Overview - Documentation
• Amazon EFS Overview - Documentation
• Amazon Q Overview - Documentation
• AWS Identity and Access Management (IAM) Overview - Documentation

Module 2: Data Processing

Websites

• Feature Engineering at Scale with SageMaker Data Wrangler
• Prepare Data at Scale Using AWS Glue Interactive Sessions
• Amazon SageMaker Clarify
• Amazon SageMaker Pipelines
• What Is Amazon SageMaker?
• Amazon SageMaker Studio
• Amazon SageMaker Notebook Instances
• Import Data into SageMaker Data Wrangler from SaaS
• Import Data into SageMaker Data Wrangler from Amazon S3
• Interactive Data Prep Widget for Notebooks
• Data preparation using Amazon EMR
• Discover EMR Clusters in SageMaker Studio
• IPython Magics
• Configuring AWS Glue interactive sessions for Jupyter and AWS Glue Studio notebooks
• Choosing the Right Data Processing Option in SageMaker
• ImgAug Rotate Augmenter
• Transform Data with SageMaker Data Wrangler

AWS Services

• Amazon SageMaker Data Wrangler Overview - Documentation
• AWS Glue Overview - Documentation
• Amazon EMR Overview - Documentation
• Amazon S3 Overview - Documentation

Module 3: Model Development

Websites

• Bring Your Own Model with SageMaker Script Mode
• What’s New in AWS EC2 Trn1 Instances
• Amazon EC2 Instance Types
• SageMaker Built-in Algorithms
• Select ML Instances on the Fly in SageMaker Studio
• SageMaker Python SDK Documentation
• Docker Containers in SageMaker
• Tune R Bring Your Own Algorithm with HPO
• Choose the Best Data Source for Your SageMaker Training Job
• SageMaker Studio Image Build CLI
• SageMaker Training Toolkit
• Why Bring Your Own Container to SageMaker
• Amazon SageMaker Experiments
• Next-Generation SageMaker Experiments
• SageMaker Supports Chart Model Training Results
• View and Compare Experiments in SageMaker
• Adapt Your Own Docker Container for SageMaker
• Built-in Rules for SageMaker Debugger
• ML Explainability with SageMaker Debugger
• Automatic Model Tuning in SageMaker
• Choosing Algorithms in SageMaker
• Hyperparameter Tuning with Hyperband
• Early Stopping in Model Tuning
• Warm Start in Model Tuning
• Best Practices for Hyperparameter Tuning
• Resource Limits in SageMaker
• Training modes and algorithm support
• Explaining Autopilot Models with SHAP
• Detect Data Bias with SageMaker Clarify
• Amazon SageMaker JumpStart Simplifies Access to Prebuilt Models
• Hugging Face on SageMaker
• AWS and Hugging Face Collaboration
• Run Automatic Model Tuning with SageMaker JumpStart
• SageMaker Debugger
• Use Built-in Rules with SageMaker Debugger

Videos

• SageMaker Script Mode Tutorial
• EC2 Instance Types Explained
• Bring Your Own Model to SageMaker
• Build and Deploy ML Models with SageMaker
• SageMaker Containers and Training Toolkit
• ML Explainability with SageMaker Debugger
• Automatic Model Tuning in SageMaker

AWS Services

• Amazon SageMaker Overview - Documentation
• Amazon EC2 Overview - Documentation
• Amazon Q Overview - Documentation
• Amazon SageMaker Debugger Documentation
• Amazon SageMaker Experiments Documentation
• Amazon SageMaker Autopilot Documentation

Module 4: Deployment and Inference

Websites

• Deploy Models from the SageMaker Model Registry
• New ML Governance Tools for SageMaker
• Improve Governance of Your ML Models with SageMaker
• Build and Manage SageMaker Pipelines Steps
• View Pipeline Execution in SageMaker Studio
• SageMaker TensorFlow Serving with gRPC
• SageMaker Shadow Testing
• Amazon SageMaker Model Registry

Module 5: Monitoring

Websites

• Model Monitor Data Capture
• Schedule monitoring jobs
• Interpreting Violations in Model Monitor
• Model Quality Monitoring with SageMaker Model Monitor
• Learn How SageMaker Clarify Helps Detect Bias
• Fairness and Explainability with Model Monitor
• Feature Attribution Drift Detection
• SHAP Values in SageMaker Clarify

AWS Services

• Amazon SageMaker Model Monitor Documentation
• Amazon SageMaker Clarify Overview

Module 6: Managing SageMaker Studio Resources and Updates

Websites

• Amazon EFS Pricing
• Amazon SageMaker Pricing
• Analyze SageMaker Spend and Determine Cost Optimization Opportunities
• Save Costs by Automatically Shutting Down Idle Resources
• Shut Down SageMaker Notebook Instances
• SageMaker Studio Auto Shutdown Extension
• Create SageMaker Studio Lifecycle Configurations
• Automatically Shut Down SageMaker Studio Apps
• Shut Down and Update SageMaker Studio Classic and Studio Classic Apps

AWS Services

• Amazon EFS Overview - Documentation
• Amazon SageMaker Overview - Documentation

Module 7: Course Wrap-up

Websites

• Machine Learning (ML) and Artificial Intelligence (AI)
• Amazon SageMaker
• AWS Certification exam preparation
• AWS Certification
• AWS Recertification
• All AWS Certification exams
• Schedule an Exam
• AWS Skill Builder subscription
• AWS Training and Certification
• AWS Online Tech Talks
• AWS Ramp-Up Guides

Courses

• Advanced Architecting on AWS Online Course Supplement
• AWS Skill Builder
• AWS Builder Labs
• AWS Workshops