Home

Course content

1. Basic programming concepts in python: variables, data containers, loops, functions, ...

2. Scientific programming with python: numpy, matplotlib, scipy...

3. Extra topics: pandas, image processing

Ideas and things to keep in mind

Feedback from previous ENI courses

1. too fast
2. more examples on programming logic, algorithmic thinking: loops (for, while), functions, strings
3. plot/organise real recording data, especially since we had many patch-clamp lectures up to that point
4. less math and more biology in the exercise
5. divide class in beginners and advanced

Proposals

• peer working, changing every lecture (1)
• learning through example (swcarpentry) (1, 2, 3, 4)
  • An introduction to Python for non-programmers using inflammation data.
• module 'turtle' for easy try and error experience
• showing some nice neuroscience applications in the beginning of the course (maybe some image processing of EM data or spike detection) (4)
• keep structure in the lectures: (1)
  • clear aim
  • short lectures
  • keep interaction with the students, through questions and simple exercises
  • summary