Course idea and structure

This course has two weekly meetings: one is solely focused on working on exercises and students can ask help from the teacher and the second one - marked as recommended attendance - includes examining exercises in small groups and going through book chapters and examples. Students must prepare to these sessions by reading assigned materials. In addition, students can use other materials to prepare or work with exercises; however see policy on AI and chat bots below.

Students are also expected to work on these exercises outside the allocated contact teaching hours.

Learning goals

By the end of the course students can

  • produce high-level problem solving strategies for real-world social science problems
  • use variables and list their potential role in problem solving
  • use control structures to solve problems
  • use data structures to help in more complex problem solving
  • use software library documentation and use software libraries understand the basic idea of computational complexity and the limits it sets to problem solving

The materials are available for both R and Python. If you have not programmed anything before, we recommend starting with R (and R Studio) in this class.

Evaluation

Students are evaluated based on the number of exercises done.

AI and chat bot policy

Can I get solutions from AI based assistant?

Please do not. The concepts we cover are essential to think about programming and computational approaches, the exercises are a tool to develop these skills, but they are not the goal, they are a mean. The competence development should not be outsourced to an external advice, such as ChatGPT. After you master them, go ahead and use these modern tools, but before, you really need to train your brains.