A Your data science project

This appendix sketches the criteria and some ideas for an interesting and engaging data science (DS) project. See also Appendix C: Data science project of the ds4psy textbook (Neth, 2023a).


Key ingredients of a successful data science project include:

  • Ask an interesting question that can be answered within a course project
  • Sketch the method or model that is suited to answer the question
  • Find or generate suitable data
  • Implement the method or model
  • Interpret your results (with summaries or visualizations)
  • Document and your methodology and conclusions (in a .Rmd-/.html-file)


Some ideas for promising data science projects include:

  • A foraging model: Compare heuristic or RL approaches in single vs. multi-agent simulations
  • Comparing strategies in games (e.g., heuristic vs. learning agents)
  • Social network analysis
  • A mate search simulation
  • Predicting the stock market (and evaluating portfolio performance)
  • Plotting text (see Section 22.3)
  • Sentiment analysis
  • Creating artistic visualizations (see Section 22.4.2)


  • Page (2018) contains dozens of models that could be implemented in simulations

  • The Learning Machines blog provides many inspirations that can be developed into projects