Knight Chair in Data Journalism
Columbia University Journalism School (CUJS)
Jonathan Soma is Knight Chair in Data Journalism at Columbia University, where he is director of both the Data Journalism MS and the summer intensive Lede Program. He lectures at Columbia on everything from basic Python and data analysis to interactive visualisation and machine learning. As an educator, programmer, and designer, he focuses on making unapproachable concepts accessible, and has worked with ProPublica, The New York Times, and others.
Summer School of Investigative Reporting 2024 Sessions
Data Journalism: Navigating the Challenges Posed by AI
Session dedicated to foundational understanding of tools and processes in data journalism: exploring data sources and visualisation techniques, and learning how to effectively navigate the challenges of data-driven storytelling, from spreadsheets to AI, while developing the skills to continue advancing.
AI Do’s and Don’ts
Explore how to responsibly use AI in modern, data-driven investigations by automating tasks like document sorting, information extraction, and transcription, while also understanding the limitations and ethical considerations to ensure balanced and accurate reporting.
Group sessions: Advanced Data Journalism
In this workshop on data analysis and cleaning with Python, you’ll learn how to use Python, Pandas, and Jupyter notebooks to efficiently process and analyse large datasets, create reproducible workflows, and uncover hidden stories, transforming your data journalism capabilities beyond the limits of Excel and Google Sheets. Learn to extract and transform hidden web data into structured datasets, covering techniques like pulling data tables, extracting articles, automating downloads, and setting up scrapers for continuous data collection using Python.