Course code: AWSMLP« Back

The Machine Learning Pipeline on AWS

This course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment. Students will learn about each phase of the pipeline from instructor presentations and demonstrations and then apply that knowledge to complete a project solving one of three business problems: fraud detection, recommendation engines, or flight delays. By the end of the course, students will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that solves their selected business problem.

 DateDurationCourse priceHandbook priceCourse languageLocation 
6/14/2021 4 2 150,00 EUR - Anglický jazyk Virtual Class
 

AffiliateDurationCatalogue priceHandbook priceITB
Praha4 2 150,00 EUR - 0
Bratislava4 2 150,00 EUR - 0

Who is the course for

  • Developers
  • Solutions Architects
  • Data Engineers
  • Anyone with little to no experience with ML and wants to learn about the ML pipeline using Amazon SageMaker

What we teach you

In this course, you will learn how to:

  • Select and justify the appropriate ML approach for a given business problem
  • Use the ML pipeline to solve a specific business problem
  • Train, evaluate, deploy, and tune an ML model using Amazon SageMaker
  • Describe some of the best practices for designing scalable, cost-optimized, and secure ML pipelines in AWS
  • Apply machine learning to a real-life business problem after the course is complete

Required skills

We recommend that attendees of this course have:

  • Basic knowledge of Python programming language
  • Basic understanding of AWS Cloud infrastructure (Amazon S3 and Amazon CloudWatch)
  • Basic experience working in a Jupyter notebook environment

Teaching methods

Professional explanation with practical samples and examples.

Teaching materials

Amazon Web Services authorized e-book included.

 

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