The Data Science with Amazon SageMaker training course is designed to demonstrate how to solve a real-world use case with Machine Learning (ML) and produce actionable results using Amazon SageMaker.
The course begins by introducing the stages of a typical data science process for Machine Learning from analyzing and visualizing a dataset to preparing the data, and feature engineering. Next, it examines the practical aspects of model building, training, tuning, and deployment with Amazon SageMaker. The course concludes by analyzing customer retention patterns to inform customer loyalty programs.
Prerequisites:
- Familiarity with Python programming language
- Basic understanding of Machine Learning
AWS Authorized Training is only available in Argentina, Brazil, Canada, Chile, Colombia, Costa Rica, Mexico, United States, and Peru.
THIS COURSE IS NOT ELIGIBLE FOR TRAINING BUNDLES.
Purpose
|
This course demonstrates how to solve a real-world use case with Machine Learning (ML) and produce actionable results using Amazon SageMaker |
Audience
|
for Developers and Data Scientists |
Role
| Data Scientist - Software Developer |
Skill Level
| Intermediate |
Style
| Workshops |
Duration
| 1 Day |
Productivity Objectives
- Prepare a dataset for training
- Train and evaluate a Machine Learning model
- Automatically tune a Machine Learning model
- Prepare a Machine Learning model for production
- Think critically about Machine Learning model results