Short Course - Python for Health, Economic and Social Science

Short Course - Python for Health, Economic, and Social Science

Short Course: Python for Health, Economic and Social Science

Course fee: £450, for students £350.

Course Description

Date: 29th September – 3rd October

By: Charles Rahal (convenor and lecturer) and Jiani Yan (Teaching Assistant)

Location: Nuffield College, Oxford

Course Description: Join us in person at the fabulous Nuffield College, University of Oxford, for a transformative week of applied programming, data science, and research translation tailored for health, economic, and social scientists. Python for Economic, Health, and Social Data Science is an intensive, fully-catered, 5-day course offering 30 hours of high-impact training in modern data analysis using Python; no prior coding experience required (at all).

Each day runs from 9:30 to 16:30, with:

• Morning lectures (9:30–12:30) introducing core programming and data concepts
• Lunch, provided at Nuffield college (12:30-13:30)
• Afternoon practical's (13:30–15:30) for hands-on coding with real-world datasets
• Research talks (15:30–16:30) by leading Python developers working at the intersection of computational research and applied global problems.

You’ll learn to write reproducible code, build statistical models, and generate insights from large-scale public datasets: skills increasingly vital for policy-relevant work in public health, social research, and economics.

Lunch and refreshments are provided daily, fostering an informal, collaborative environment in the heart of Oxford’s academic community.

Course content by day:

• Day 1: Python object fundamentals — variables, collections, logic, and control flow;
• Day 2:  For loops, error handling, functions, file I/O.
• Day 3: Mathematical calculations, web scraping, data wrangling, and exploratory analysis;
• Day 4: Modelling basic kinds of data and visualising patterns with matplotlib;
• Day 5: More advanced data modelling, machine learning, natural language processing, multiverse analysis, and more (time permitting).

By the end of the course, you’ll be confident in navigating Python’s data science ecosystem and applying it rigorously to your own empirical questions. Whether you're a researcher, student, or professional, this course is your launchpad for computational social science. Attendance will be recognised through [Accredible] badges.

To register for this course, please click [this link]. 

Please send any queries to teaching@demography.ox.ac.uk. We look forward to warmly welcoming you!