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Machine Learning Pipelines 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.

Intended Audience

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

Delivery Method

This course is delivered through a mix of:

  • Instructor-led training
  • Hands-on labs
  • Demonstrations
  • Group exercises

Course Prerequisites

We recommend that attendees of this course have the following prerequisites:

  • 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

Machine Learning Pipelines on AWS Key Facts
Course Duration (days)

4.00

Course Price (ex VAT)

£2805.00

Course Vendor

Amazon

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