The Machine Learning Pipeline on AWS

Course overview

This course explores how the machine learning (ML) pipeline can be used to solve a real business problem in a project-based learning environment. Participants will learn about each phase of the pipeline through presentations and demonstrations by the instructor, and then apply this knowledge to complete a project addressing one of three business problems: fraud detection, recommendation engines, or flight delays. By the end of the course, participants will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that addresses their chosen business problem. Course content includes: - Suitable ML approach for a specific business problem - ML pipeline to solve a specific business problem - Training, evaluating, deploying, and tuning an ML model with Amazon SageMaker - Best practices for designing scalable, cost-optimized, and secure ML pipelines in AWS You will have access to the labs for an additional 4 weeks after the course, allowing you to repeat exercises or delve deeper individually.

Upcoming dates

• 2026-08-03T22:00:00.000Z · 2026-08-06T22:00:00.000Z · Virtuelles Klassenzimmer
• 2026-08-03T22:00:00.000Z · 2026-08-06T22:00:00.000Z · Düsseldorf · Präsenzunterricht
• 2026-11-02T23:00:00.000Z · 2026-11-05T23:00:00.000Z · München · Präsenzunterricht
• 2026-11-02T23:00:00.000Z · 2026-11-05T23:00:00.000Z · Virtuelles Klassenzimmer