This course teaches you how to design, evaluate, and operate reliable machine learning data pipelines in production. You’ll learn how daily ETL and ELT pipelines feed feature stores, how orchestration supports reproducible feature engineering, how to handle upstream schema changes without breaking downstream systems, and how to evaluate pipeline health using freshness, lag, and SLA metrics. Designed for data engineers, analytics engineers, and ML practitioners, the course builds job-ready judgment for delivering timely, trustworthy, and resilient data to ML systems.
Orchestrate, Analyze, and Evaluate ML Pipelines
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
2 hours to complete
Flexible schedule
Learn at your own pace
Details to know
Shareable certificate
Add to your LinkedIn profile
Recently updated!
March 2026
Taught in English
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There is 1 module in this course
This course teaches you how to design, evaluate, and operate reliable machine learning data pipelines in production. You’ll learn how daily ETL and ELT pipelines feed feature stores, how orchestration supports reproducible feature engineering, how to handle upstream schema changes without breaking downstream systems, and how to evaluate pipeline health using freshness, lag, and SLA metrics. Designed for data engineers, analytics engineers, and ML practitioners, the course builds job-ready judgment for delivering timely, trustworthy, and resilient data to ML systems.
What's included
6 videos3 readings4 assignments
Instructor
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