Course repository for the Fall 2025 edition of Introduction to Python for Neuroscientists, run by the Columbia Neurobiology and Behavior PhD program.
Course description: This class will give students a general and applied introduction to Python within the context of neuroscience. Topics covered will include setting up python, using git to track and publicize work, programming basics, data manipulation and visualization, machine learning, and navigating existing codebases. The course will culminate in a project where students will analyze data of their choice in Python (options will be provided for students who don’t have their own datasets). Students will then work to understand each other’s projects to get experience reading and understanding each others’ code, and to incentivize good documentation. Students will present their work to the class.
Course Structure: Classes will consist of live programming and instruction, alongside optional out-of-class homework (see important dates below for details). Pair and group-programming will be used in addition to individual programming. Please bring your laptop – if you do not have one / that will be an issue, please contact us.
Prerequisites: No background in programming or math is required. All we ask is that you come with a desire to learn :)
Grades will be based on participation and the final project.
Email: pfncolumbia@gmail.com
Important dates:
- By 9/2: Watch pre-videos, setup computer, and make a github account following these instructions.
- Weeks 6-7: set up a time if you want to discuss your project with us
Schedule (subject to change):
- Go beyond what we covered in Week 1 with Git, Command Line, Shell, Code Editors and more with The Missing Semester of Your CS Education from MIT
- The Good Research Code Handbook by Patrick Mineault -- good principles for writing research code in a quick and enjoyable read. He also provides information about good tools that are good to explore if you are coding regularly.