OCI Data Science Professional is about building ML systems that work in production: data handling, training/evaluation discipline, secure deployment, and monitoring.
What you should be able to do
- Navigate OCI Data Science concepts: projects, notebooks, jobs, models, and deployments.
- Store and access datasets and artifacts safely (Object Storage + IAM boundaries).
- Reason about evaluation metrics, overfitting, and leakage at a practical level.
- Deploy models, monitor quality/latency/cost signals (concept-level), and roll back safely.
- Apply governance: versioning, approvals, auditability, and least privilege.
Efficient prep strategy
- Use the Syllabus as your checklist.
- Focus on lifecycle thinking (train → evaluate → deploy → monitor).
- Drill scenarios; correct answers include both technical steps and governance guardrails.