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AWS Classroom Training

Practical Data Science with Amazon SageMaker

Understand a day in the life of a data scientist from an expert AWS instructor

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Practical Data Science with Amazon SageMaker

As artificial intelligence and machine learning (AI/ML) are quickly becoming part of our day-to-day, it is becoming increasingly more important to understand how to collaborate efficiently with data scientists and build applications that integrate with ML.

The Practical Science with Amazon SageMaker course will help you in your developer or DevOps engineer role understand the basics of ML and the steps involved in building ML models using Amazon SageMaker Studio. In this one-day, classroom training course an expert AWS instructor will walk you through how to prepare data and train, evaluate, tune, and deploy ML models.

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Course details

  • Level: Intermediate
  • Type: Classroom (virtual and in person)
  • Length: 1 day
  • Discuss the benefits of different types of machine learning for solving business problems
  • Describe the typical processes, roles, and responsibilities on a team that builds and deploys ML systems
  • Explain how data scientists use AWS tools and ML to solve a common business problem
  • Summarize the steps a data scientist takes to prepare data and train, evaluate and tune, and deploy ML models
  • And much more
  • Development operations (DevOps) engineers
  • Application developers

We recommend that attendees of this course have:

This course is offered in the following languages: Bahasa Indonesia, English, French (France), German, Italian, Japanese, Korean, Portuguese (Brazil), Simplified Chinese, Spanish (Latin America), and Traditional Chinese.

We regularly update our courses based on customer feedback and AWS service updates. As a result, course content may vary between languages while we localize these updates.