The Machine Learning Pipeline on AWS

Unlock the power of the machine learning pipeline on AWS and elevate your skills with hands-on projects in fraud detection, recommendation systems, and flight delay predictions.

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Essential Skills Gained

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Understand the phases of the machine learning pipeline.

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Apply Amazon SageMaker for real-world ML model deployment.

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Evaluate and tune models to solve business problems.

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Deploy machine learning solutions effectively using AWS infrastructure.

Format

  • Instructor-led
  • 4 days with lectures and hands-on labs.

Audience

  • Developers
  • Solutions architects
  • Data engineers
  • Beginners in ML using Amazon SageMaker

Description

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.

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Upcoming Course Dates

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Course Outline

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Module 1: Introduction to Machine Learning and the ML Pipeline

Module 2: Introduction to Amazon SageMaker

Module 3: Problem Formulation

Module 4: Preprocessing

Module 5: Model Training

Module 6: Model Evaluation

Module 7: Feature Engineering and Model Tuning

Module 8: Deployment

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