Lecturers: Dr Jonathan Cardoso-Silva and Dr Stuart Bramwell
Is London really all that rainy? You'll answer this question by collecting live weather data, cleaning it with Python, and building a narrative report. This will be your first project to make it fun to learn the skills taught in this course.
You'll learn the data engineering skills that social scientists actually use in their research. The course covers collecting data from APIs, cleaning it with Python and pandas, storing it with SQL, and presenting findings through visualisations and web dashboards.
🌟 Designed for mixed backgrounds: Complete coding beginners work alongside students with programming experience. You'll focus on understanding why each technique works. This builds thinking skills that transfer across different tools and contexts.
What you'll learn:
- Professional workflow: Git/GitHub for version control, cloud platforms, and reproducible analysis
- Data collection: APIs, authentication, and handling real-world data sources
- Data transformation: Python, pandas, and SQL for cleaning and restructuring data
- Communication: Interactive dashboards and data storytelling for social science research
Your final project: A complete data analysis you build yourself. You'll collect live data, structure it professionally, and present insights through an interactive web application. You'll understand the engineering principles behind every decision you make.
Assessment: Two hands-on projects (25% midterm, 75% final). We mark your understanding and professional practice rather than perfect code.
