Learning Path
Ray Applied AI Researcher
Explore RLlib, distributed experiments, and Serve-based application patterns for research teams moving toward production.
3 coursesCapstone certificate5.5 hoursApplied AI and research engineers
What you'll cover
- RLlib for Applied Teams
- Ray Train and Tune for ML Teams
- Ray Production Readiness Certificate
- RLlib loop
- Policy lifecycle
- Worker groups
Available in this academy.
You can jump directly into any course or lesson in the path.
Course Sequence
3 steps1
Step 1
RLlib for Applied Teams
Understand RLlib experiment structure, evaluation discipline, and policy checkpoint lifecycle.
1.5 hours2 modules4 lessonsProgress tracking available
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Step 2
Ray Train and Tune for ML Teams
Coordinate distributed training jobs and credible hyperparameter experiments with Ray Train and Ray Tune.
2 hours2 modules4 lessonsProgress tracking available
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Capstone Certificate
Ray Production Readiness Certificate
Demonstrate readiness to design, review, and operate Ray workloads across Core, Data, Train, Tune, Serve, and RLlib.
1 hour1 modules2 lessonsCertificate assessment
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