Learning Path
Ray ML Engineer
Scale training, tuning, batch inference, and online serving with clear model lifecycle handoffs.
3 courses7 hoursML engineers
What you'll cover
- Ray Data for Batch AI
- Ray Train and Tune for ML Teams
- Ray Serve for Online AI
- Data ingestion
- Batch inference
- Worker groups
Available in this academy.
You can jump directly into any course or lesson in the path.
Course Sequence
3 steps1
Step 1
Ray Data for Batch AI
Design Ray Data pipelines for parallel ingest, preprocessing, offline inference, and reliable outputs.
2 hours2 modules4 lessonsProgress tracking available
View course2
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
View course3
Step 3
Ray Serve for Online AI
Build Serve applications with deployment graphs, request routing, autoscaling, and LLM-ready controls.
2 hours2 modules4 lessonsProgress tracking available
View course