COMPSS 201
Introduction to Computing
The Master of Computational Social Science program requires students to be proficient in the basic computing skills required for computational social science — this class aims to bring all entering students up to the required level of proficiency. It covers the process of setting up a computing environment for data science tasks, usage of Python for scientific programming, the ecosystem of common Python packages for data science tasks, accessing data from different types of files, databases, and web scraping, APIs, and computing on remote systems.
Topics
- Set-up a computing environment appropriate for conducting data science analyses using Python and the ecosystem of Python data science packages Write modular, performance and idiomatic Python code for data science tasks Determine which Python packages are appropriate for analyzing a given data set in tabular, image, textual, structured, geographic or network format Transform data from various sources into a form appropriate for analysis and training machine learning models Recognize the applicability and make use of techniques for extracting, scraping and crawling web data Design the processing of computing tasks for distributed and remote systems
Official catalogue course objectives and student learning outcomes
Sources
- Course catalogue ↗2026-2027