Validate your ML expertise with the only official scikit-learn certification.
Official, proctored, hands-on certifications designed by the people who maintain scikit-learn. Train with Skolar. Get assessed on real ML work. Earn a verifiable credential.
What is your scikit-learn level?
120 minutes, coding plus theory, documentation allowed, online or at test centers, verifiable badge.
Associate Practitioner
Best for: Practitioners with foundational scikit-learn experience and early-career data scientists.
You are able to:
- Build end-to-end pipelines
- Apply correct preprocessing and evaluation
- Avoid common leakage and validation mistakes
Professional Practitioner
Best for: Practicing data scientists working on real ML projects.
You are able to:
- Design robust pipelines under real constraints
- Tune models and evaluate them correctly
- Apply best practices consistently across projects
Expert Practitioner
Best for: Senior practitioners and ML experts.
You are able to:
- Debug and reason about complex ML workflows
- Write and use advanced scikit-learn components
- Make informed design trade-offs in production contexts
Train with the same standards you will be evaluated on.
Skolar provides structured learning paths and hands-on exercises aligned with the certification expectations.
Things candidates ask before they sit.
Still unsure? Our certification team will get back to you.
The credential the maintainers sign.
Three levels. One library. Real ML work, scored against the standards the people who ship scikit-learn use every day.
Stop shipping broken models. Start deciding together.
Track your first experiment in 5 minutes. No sign-up required, no vendor lock-in. Open source, built on scikit-learn.
