Musashi Jacobs-Harukawa, Department of Politics and International Relations
Introduction to Python for Social Science is an 8-week optional methods module aimed at social science researchers seeking to learn programming skills for their research. There will be weekly lectures, lasting 60 to 90 minutes, followed by a workshop, and supplemented by weekly office hours. All of the above will be conducted on Teams.
The aim of this course is two-fold. The first goal is to teach students essential data analysis and scripting skills so that they are able to put together short programs and run their own analyses. The second aim is to give a introduction to the numerous techniques and technologies that researchers can integrate into their own research, and to provide incentives to invest in computational methods and skills. Some of the techniques that will be taught include:
- Using Python as a Research and Development Tool
- Data Cleaning and Merging with
pandas - Static Data Visualisation with
matplotlibandseaborn - Introduction to Machine Learning with
scikit-learn - Introduction to Web Scraping with
beautifulsoupandselenium
Note that this course is not a course in programming. Students will learn how to use Python for data analysis and research, but the primary focus is on teaching them about the available methods and the bare minimum level of programming to implement these methods. Also note that this course is optional, and there will be no marked assignments, but there will be weekly tasks designed to aid learning. Students are encouraged to complete these tasks, and to ask questions about them during the workshop and clinic.
This course is aimed at complete beginners, although experience with other programming languages (such as R) may provide some useful reference points. As spaces are limited, priority will be given to students without prior experience using Python, and those who have a use case for computational tools in their research.
This repository contains all of the code, lecture slides, and jupyter notebooks for the course. You are welcome to clone this repository/browse the material here, but I've also made the effort to let you browse the slides in the browser at muhark.github.io/dpir-intro-python. I am also working on Google colab integration to allow students to work with the notebooks interactively from the website.