AWS - The Machine Learning Pipeline on AWS

This course explores how to the use of the iterative machine learning (ML) process pipeline to solve a real business problem in a project-based learning environment. Students will learn about each phase of the process 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.

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In this course, you will:

 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

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