ACNEI Computational Neuroscience Introductory School | May 2026
Instructor: Jessica Oparebea · University of Ghana
This is the companion notebook repository for Python Tutorial I at the ACNEI Computational Neuroscience Introductory School. It is designed for neuroscience students and researchers who are new to Python and want to use it as a tool for data analysis and modelling.
All examples use neuroscience themed data; spike trains, membrane potentials, brain regions, EEG signals. So you are learning Python and building intuition for the kinds of data you will work with as a computational neuroscientist.
| # | Notebook | Topics |
|---|---|---|
| 01 | Setup & First Steps | Python setup, Jupyter, first print statement |
| 02 | Variables & Data Types | int, float, str, bool, arithmetic, f-strings |
| 03 | Data Structures | Lists, Tuples, Dictionaries, Sets |
| 04 | Flow Control | if/elif/else, for loops, while, break/continue |
| 05 | Functions | def, return, defaults, *args, **kwargs, lambda |
| 06 | Libraries | math, numpy, matplotlib — with neuroscience plots |
Solutions to all exercises live in the
solutions/folder.
Click any notebook and then click the "Open in Colab" badge at the top of it.
# 1. Clone the repo
git clone https://github.com/JessicaOparebea/acnei-python-course.git
cd acnei-python-course
# 2. Install dependencies
pip install -r requirements.txt
# 3. Launch Jupyter
jupyter notebookSee requirements.txt. Core packages:
numpymatplotlibscipyjupyter
By the end of this tutorial, you will be able to:
- Write and run Python code in a Jupyter notebook
- Use variables, data types, and data structures confidently
- Write reusable functions
- Import and use scientific libraries
- Visualise neuroscience data with matplotlib
- Neuromatch Academy — Python + Computational Neuroscience
- Python Official Docs
- NumPy Quickstart
- Matplotlib Gallery
- Fabri Damicelli's Python Course
Developed for the ACNEI Computational Neuroscience Introductory School