Data Science in Practice or Neurophysiological Data#

Data Science in Practice for Neurophysiological data is an open set of materials for learning introductory data science for psyM1.

Overview#

The goal of Data Science in Practice is to introduce the practical elements of doing data science with a focus on neurophysiological data. Data science is an emerging and multidisciplinary field, organized around the practice of analyzing data, and all the questions, practices and problems that entails. These materials focus on the practical elements of finding, analyzing, interpreting and contextualizing data analysis, in order to practice answering questions with data.

Topics#

  1. Python and how to write it (s00-s01)

  2. Basic data operations (s02-s03)

  3. Statistic in Python (s04-s06)

  4. Neurophysiological data (s07-?)

Dates#

14 seminar sessions in total.
25.10.2022 - 07.02.2023 (No sessions 27.12. & 03.01.)
Tuesdays 10:15-11:45.
We meet every week online here.
Room 315 in OS62 is reserved if you dont want to do the course from home.
The final exercises must be handed in until 28.02. 23:59:59. The evaluation from the seminar can be found here.

Content#

Available materials include:

  • Theory which introduce key topics for doing data science

    • These can be used to explore and learn about key topics

  • Assignments which are problem sets that can be worked through

    • These can be used to practice key skills and ideas with code

Session plan#

  1. Joined coding of old assignments as presentations (~20-30-min)

  2. New theory and assignments (~45 min)

  3. Feedback session (15 min)

All the materials for psyM1-2 are listed in the table of contents in the left sidebar. Note that these materials are not created as fully detailed descriptions or formal descriptions of the topics they introduce.

How to Use These Materials#

These materials are created as Jupyter Notebooks, and are intended to be executed and explored in a hands-on manner. There is a download link at the top left of the page, that can be used to download each page as a notebook. This allows you to use the notebook locally, executing code, and answering questions.

Issue Tracking#

If you have any find any bugs or issues, or have any suggestions for these materials, please open an issue.

Source Materials#

This set of materials is an openly available version of the master course (psyM1-2) in psychology thaught at Kiel University.

Designing and curation of scientific data projects is based on The Good Research Code Handbook by Patrick J Mineault.

The idea for the analysis of electrophysiological data is inspired by Neuroscience tutorials from Marijn van Vliet.

Reference#

This content of the course is partially described in the following paper:

Donoghue T, Voytek B, & Ellis S (2022). Course Materials for Data Science in 
Practice. Journal of Open Source Education, 5(51), 121. DOI: 10.21105/jose.00121

License#

The materials on this website are openly available under a CC-BY 4.0 license.