Date: 22 Jun, 2021
Duration: 1 Day

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.

Course Objectives
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

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