Data Science with Amazon SageMaker

Overview
In this intermediate-level course, you will learn how to solve a real-world use case with machine learning (ML) and produce actionable results using Amazon SageMaker. This course walks through the stages of a typical data science process for machine learning from analyzing and visualizing a dataset to preparing the data, and feature engineering. Individuals will also learn practical aspects of model building, training, tuning, and deployment with Amazon SageMaker. A real life use case includes customer retention analysis to inform customer loyalty programs.

In this course, you will learn how to:

• 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
• And much more

Intended Audience
This course is intended for:

• Developers
  
• Data scientists

We recommend that attendees of this course have:

• Familiarity with Python programming language
• Basic understanding of machine learning