Machine Learning Engineering on AWS
AWS-MLEA
M00
Course Introduction
M01
Introduction to Machine Learning
M02
Analyzing ML Challenges
M03
Data Processing for Machine Learning
M04
Data Transformation and Feature Engineering
M05
Choosing a Modeling Approach
M06
Training ML Models
M07
Evaluating and Tuning ML Models
M08
Model Deployment Strategies
M09
Securing AWS ML Resources
M10
MLOps and Automated Deployment
M11
Monitoring Model Performance and Data Quality
M12
Course Wrap-Up
D1R
Day 1 Review
D2R
Day 2 Review
Lab Walkthrough
Esercitazioni pratiche guidate passo-passo
Lab 1
Analyze and Prepare Data with SageMaker Data Wrangler and Amazon EMR
Lab 2
Data Processing Using SageMaker Processing and the SageMaker Python SDK
Lab 3
Training a Model with Amazon SageMaker AI
Lab 4
Model Tuning and Hyperparameter Optimization
Lab 5
Shifting Traffic
Lab 6
Using SageMaker Pipelines and the Model Registry
Lab 7
Monitoring a Model for Data Drift