Good Coding Practice in Neuroscience
Many scientists picked up programming in the course of their day-to-day work. They often learn from peers or supervisors, who in turn have never done formal courses in programming. This leads to many entrenched problems in the quality of code and programming style.
This training, led by Dr Sanjay Manohar (University of Oxford), will provide a practical foundation in writing clean, reusable, and well-documented code. Using examples mainly in Python, MATLAB, and R, the session will highlight common pitfalls and introduce strategies to improve the quality of your programming.
Topics included in this session:
• Optimising your programming environment
• Naming conventions
• Commenting and version control
• Code structure and conceptualisation
• Functions and interfaces
Topics included in a later advanced session:
• Data handling
• Code efficiency
• Errors, and why they can be useful
Learning outcomes:
By the end of this training, participants will:
• Be confident using a variety of techniques for good coding
• Understand the strengths and weaknesses of different programming styles
• Know how to write code that is shareable, reusable, functional, efficient, and well-documented
Format: Online (Zoom)
Date: 27th November 2025
Time: 2–5pm
Course leader:
