I've been accepted into a combined B.A./M.A. program focused mainly on political science, international relations, and the history of the SWANA region. I'll be starting in October and want to use my free time to build practical programming skills that could help with coursework, a future thesis, research, and possibly employment.
I already have some experience with Python, Pandas, and Matplotlib, but I'd like to become more proficient. I'm also considering learning SQL and Git. Should I stay focused on Python, or would SQL be particularly useful for research and data analysis? How much time should I invest in Git, and is this overall direction worthwhile for someone who isn't studying computer science? I'd appreciate advice on what to learn and, ideally, how to practice it through useful projects.
3 Answers
Git is definitely worth learning, but it shouldn’t be treated like another huge programming subject. You can learn the essentials in an afternoon: initialize or clone a repository, add files, commit changes, view history, and restore earlier versions. It’s essentially a reliable save-point system for projects.
You can use it for code, notes, essays, Markdown files, and other text-based work. Start with small personal projects and get used to committing regularly. Branches and more advanced collaboration workflows can come later if you need them.
Keep building on Python, since you already know the basics and it’s widely useful for research. Try applying it to projects you genuinely care about: cleaning public datasets, analyzing election results, visualizing demographic trends, or collecting and comparing historical data. That will teach you more effectively than only following courses.
SQL is worth learning too, but you probably only need a solid working knowledge at first. Learn how to filter, join, aggregate, and group data, then expand as your projects require it. For data analysis involving large, structured datasets, SQL can become much more important than this answer suggests, so don’t dismiss it entirely.
That makes sense. My interest is mainly research and analysis rather than software development, so I’ll focus on using Python and SQL on actual political or historical datasets instead of trying to learn programming in the abstract.
The best course is probably one that leads to a finished project rather than a long list of disconnected tutorials. Keep Python as your main language, learn enough SQL to work with real databases, and practice with tools such as Jupyter, Pandas, visualization libraries, and basic statistics.
For your field, the combination of research methods and technical ability can be valuable even if you never become a professional programmer. A portfolio showing clear questions, clean data, reproducible analysis, and honest conclusions will be more useful than simply collecting certificates. Choose a topic related to your interests and build a few complete analyses from publicly available data.
I hadn’t considered using Git for notes and writing as well as code, but that sounds useful. I’ll start with the basic version-control workflow and expand from there.