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Machine Learning Pipeline on AWS (ML-PIPE)

 

Who Should Attend

This course is intended 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

Prerequisites

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

Course Objectives

In this course, you will learn 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

Course Content

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.

Online training

Duur 4 dagen

Prijs (excl. BTW)
  • 2.495,- €
Klassikale training

Duur 4 dagen

Prijs (excl. BTW)
  • Nederland: 2.495,- €
  • België: 2.495,- €

Op dit moment is deze training niet beschikbaar in het open rooster. De kans is echter groot dat wij u toch een passende oplossing kunnen bieden. Wij horen graag wat uw specifieke wensen zijn. U bereikt ons via 030 658 2131 of info@flane.nl. We helpen u graag!  Vraag een datum aan