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The Machine Learning Pipeline on AWS Course Overview

The Machine Learning Pipeline on AWS course provides a project-based learning environment to explore the iterative machine learning (ML) process pipeline for solving real business problems. Participants will learn about each phase of the pipeline through instructor presentations and demonstrations. They will then apply this knowledge to complete a project focusing on fraud detection, recommendation engines, or flight delays. Throughout the course, participants will build, train, evaluate, tune, and deploy an ML model using Amazon SageMaker to solve their chosen business problem. The course is designed to be accessible for learners with limited or no machine learning experience. A basic understanding of statistics will be helpful for the course. By the end of the course, participants will have gained practical experience in the end-to-end ML pipeline and successfully developed an ML model using Amazon SageMaker to address their selected business problem
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Course Introduction

Price:

USD 900

Duration:

24 Hrs.

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

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