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Python Course 2026

This repository contains information about the course "Basic Programming - Introduction into Python" (2026).

Acknowledgments

In this class, we will follow largely (but not exclusively) the course NESC 3505 Neural Data Science, developed at Dalhousie University as an open educational resource.

Course structure

Approach

The first part of the course follows an inverted classroom approach, which means you prepare the material for the sessions at home, leaving the actual sessions for doing exercises, discussions, questions, and problem-solving. The second part of the course - after the vacation - consistst of more advanced sessions that will address more specific topics, such as the use of AI, data processing and presentation for neuroscience, how to design (re)usable software and such.

Schedule

Materials

The materials consist of

  • Online chapters, which will provide you with the respective background
  • Jupyter notebooks, in which you can learn and practice Python concepts
  • YouTube videos, which go through the notebooks step-by-step. We highly recommand to try to do the notebooks first by yourself, and only use the videos if you encounter major difficulties

When indicated below, you need to read a few chapters and do the lesson part of the respective Jupyter notebooks before the session. The notebooks are divided into a lesson part, where the concepts are introduced and demonstrated, and an exercise part, where you can apply the knowledge just gained.

During the sessions, we will to the exercise parts of the notebooks together, discuss what you learned, where you encountered problems, and how to solve these.

Important: The links to chapters point at the original class material, whereas the notebooks you will find in your bwJupyter environment - as demonstrated in the first session.

Important link(s)

Link to bwJupyter environment

17.4. | Introduction, Setup, Project overview

To prepare before:

During the class:

  • Why this course? About adult learners and your motivation to learn Python, your programming/Python background, that the only way to learn to code is to write it, the importance of coding skills for science and beyond, and the use of AI tools.
  • The organisation of this course. Time budget outside the classroom, videos as the last resort, and final project.
  • Setting up bwJupyter.de_ and accessing the course material. How to submit exercises.
  • Skills evaluation

02.05. | Variables & Assignment, Data Types & Conversion, Python Built-ins, Lists, Dictionaries

To prepare before:

  • Read chapter "Introducing Python"; you can ignore the section Deactivate AI for Now. Also, read the next chapter with the respective learning objectives.
  • On bwJupyter: Go over the notebooks 01 - Variables and Assignments to 05 - Dictionariesunder__shared`. Note that the exercise parts of the notebooks will be done in class.

During the class:

  • Do exercises together, answer qustions.