ML Pipeline with Amazon Personalize you own this product

basic AWS cloud computing • advanced shell scripting • basic Python
skills learned
create a data lake S3 bucket using an AWS CloudFormation template (Infrastructure as Code) and prepare data using AWS Glue • design a data pipeline to create and train an Amazon Personalize solution • deploy the pipeline using AWS Step Functions and AWS CloudFormation (Infrastructure as Code)
Mike Shakhomirov
1 week · 6-8 hours per week · BEGINNER

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Help your company’s messenger application provide better product recommendations for its customers. As a data engineer at the company, your task is to create a machine learning (ML) pipeline using the Amazon Personalize service. You’ll use CloudFormation templates to create a repository for the required AWS infrastructure resources, and AWS Glue to transform the raw user engagement data. Using Amazon Personalize, you’ll import a dataset and create and train the Amazon Personalize ML model for your users’ recommendations. To complete the project, you’ll create a workflow to train your Amazon Personalize recommendation solution using AWS Step Functions and user engagement events. When you’re done, you’ll have designed an ML pipeline using the Amazon Personalize API that provides product recommendations that suit your users best.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Mike Shakhomirov

Mike Shakhomirov is the head of data engineering at The World's Online Festival. He has an MBA as well as a diploma in big data and social analytics from MIT, and he’s a Google Cloud Certified Professional Data Engineer. Passionate, enthusiastic, and digitally focused, he loves the challenges that the diverse gamut of digital marketing can offer. Mike is an official writer for publications including Towards Data Science and The Startup, and he’s the author of more than 50 published articles on topics such as data engineering, machine learning, and AI in digital marketing. You can find him on LinkedIn and Medium.


This liveProject is for intermediate Python programmers who are interested in building an ML data pipeline using AWS.

  • Basic Python skills and knowledge
  • Advanced shell scripting skills
  • AWS account
  • Basic cloud computing skills
  • Basic knowledge of the MySQL database
  • Basic knowledge of AWS Lambda serverless infrastructure


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