Author: Richard Foltyn, University of Glasgow
This introductory course consists of several units. Each unit corresponds to one interactive Jupyter notebook, which is also available as a static PDF file. Alternatively, you can download the entire course as a single PDF.
Unit | Title | Google Colab | |
---|---|---|---|
1 | Language and NumPy basics | ||
2 | Control flow and list comprehensions | ||
3 | Reusing code - Functions, modules and packages | ||
4 | Plotting | ||
5 | Advanced NumPy | ||
6 | Handling data with pandas | ||
7 | Data input and output | ||
8 | Random number generation and statistics | ||
9 | Introduction to unsupervised learning | ||
10 | Introduction to supervised learning | ||
11 | Error handling (optional) |
Detailed slides on how to set up your working environment are available here.
This material is licensed under a
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License,
except for the data files contained in the data/
folder, which
fall under the terms imposed by the original content creators.
Special thanks go to Jonna Olsson for reading through all units and suggesting various improvements.