Sign inFree 3-minute machine learning skill check. Test your knowledge of overfitting, evaluation, metrics, optimisation, and regularisation — instant results.
What this check covers
Generalisation
Knowing why models overfit is the first thing interviewers test.
Evaluation
Honest evaluation methodology separates reliable models from lucky ones.
Metrics
Choosing the right metric for imbalanced data is a common interview trap.
Optimisation
Understanding gradient descent is essential for debugging training issues.
Regularisation
Regularisation is your primary tool against overfitting in practice.
This platform is built to get you into roles like ML Engineer — this quick check is step zero.
You get an instant snapshot of your strengths and the exact gaps to close next.
No account, no code, no pressure — just an honest read on where you're starting from.
The course
9 modules · 45 lessons · 10 hands-on projects. Your placement result maps straight onto this path.
Outcomes
The skill check is just the on-ramp. Finish the track and you leave with proof, not just knowledge.
A working project, graded
Build a real project and get an AI review against a professional rubric.
A verified skill profile
See exactly where you stand across the competencies employers test for.
Production-grade patterns
Learn the patterns teams actually ship — not toy demos.
A portfolio you can share
Completed projects live in a public portfolio you can send to employers.
A certificate on completion
Earn a shareable certificate when you finish the track.
Overfitting and generalisation, train/test splitting, metrics for imbalanced datasets, gradient descent, and regularisation (L1/L2).
No code is required for this quick check. The full assessment includes hands-on coding challenges.
This is a 5-question snapshot. The full assessment has 20 questions including code exercises, is AI-graded, and builds a personalised learning plan.
Find your starting point as a ML Engineer — instantly, no signup.