Skills you’ll practise
Grouped from the public exam objectives published by Red Hat.
- OpenShift AI architecture and MLOps concepts
- Data science projects, workbenches and custom images
- Data connections to S3 and databases
- Node placement for workbenches and model servers
- Model serving
- Model registry and versioning
- Monitor bias and drift
- Data science pipelines
- Model compression and LLM evaluation
- RAG, agentic and guarded generative AI apps
Planned labs
10 labs in preparation- 01Coming soon
OpenShift AI architecture and MLOps concepts
Real machine · guided tasks · automatic checks
- 02Coming soon
Data science projects, workbenches and custom images
Real machine · guided tasks · automatic checks
- 03Coming soon
Data connections to S3 and databases
Real machine · guided tasks · automatic checks
- 04Coming soon
Node placement for workbenches and model servers
Real machine · guided tasks · automatic checks
- 05Coming soon
Model serving
Real machine · guided tasks · automatic checks
- 06Coming soon
Model registry and versioning
Real machine · guided tasks · automatic checks
- 07Coming soon
Monitor bias and drift
Real machine · guided tasks · automatic checks
- 08Coming soon
Data science pipelines
Real machine · guided tasks · automatic checks
- 09Coming soon
Model compression and LLM evaluation
Real machine · guided tasks · automatic checks
- 10Coming soon
RAG, agentic and guarded generative AI apps
Real machine · guided tasks · automatic checks
OpenShift AI mock exam
A full timed practice exam on fresh machines, graded automatically, with a score per skill.
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