Challenges

382 exercises.
Every one of them graded.

Each challenge is a small task with a checker behind it — you write the code, press Check, and it compares what you produced against the answer. Nothing is graded on the text of your code, so there is always more than one way to be right.

NumPy

0/104

Arrays, shapes and broadcasting — the layer everything else is built on.

pandas

0/109

Labelled data: indexes, filtering, and split-apply-combine.

Matplotlib

0/62

Figures, axes and artists — what actually draws your chart.

Machine Learning

0/107

The core ideas, made visible — with scikit-learn.

Solving a challenge here marks it solved in its lesson too — it is the same exercise, and 382 of them exist in total. If a task makes no sense on its own, the lesson that teaches it is linked from every challenge page.