This learning path provides you with an introduction to the Amazon SageMaker service followed by the opportunity to practice using SageMaker in a series of practical hands-on labs. 

Learning Objectives

• Understand the key services of Amazon SageMaker
• Learn how to use training data sets with machine learning models in SageMaker
• Understand how machine learning concepts can be applied to real-world scenarios
  

Intended Audience

This learning path is intended for anyone who is:

• Interested in understanding how to deploy machine learning models on a managed service like Amazon SageMaker
• Looking to enrich their understanding of machine learning and how to use it to solve complex problems
• Looking to build a foundation for continued learning in the machine learning space and data science in general

Prerequisites

To get the most out of this learning path, you should have a general understanding of data concepts as well as some familiarity with Amazon Web Services. Some experience in data or development is preferable but not essential. 

Feedback

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