You’ve reached the bridge between core Python and machine learning. NumPy is the library that all of scientific Python is built on — Pandas, scikit-learn, PyTorch, TensorFlow, every one of them uses NumPy arrays under the hood.
This section is a focused introduction: enough to be comfortable, not a complete reference.
What’s in this section
- Arrays — create, inspect, reshape
- Array operations — element-wise maths without loops
- Broadcasting — how NumPy combines arrays of different shapes
- Indexing and slicing — pick out exactly the values you want
- Vectorisation — why NumPy is so much faster than plain loops
By the end of this section, you’ll be ready for a follow-up course on Pandas, data analysis, or your first machine learning model.