A Critical Introduction to Python for Data Science

Sonia Fereidooni

Sonia is a Gates Cambridge and PhD student studying the sociotechnical impacts of Generative AI on the Global South, particularly the military-industrial-academic supply chain that allows AI to be weaponised through its integration with lethal autonomous weapon systems in global conflict settings. Sonia completed her BS in Computer Science & Data Science, BA in Sociology, and MS in Computer Science & Engineering at the University of Washington. Her research has spanned AI Bias, Commonsense Reasoning, improving unsupervised Computer Vision models, and designing equitable Computer Science education. Sonia previously worked as a Research Engineer at Google Brain and DeepMind, developing and open-sourcing the AI/ML development frameworks T5X and SeqIO. She was also a Responsible AI Research Fellow at Google’s Impact Lab involved in analysing systemic biases within Google’s search algorithms, and she served as a researcher at the Allen Institute for AI (Ai2) working on the Mosaic Team researching commonsense reasoning in AI models.

This Digital Methods Workshop will guide participants through critical social analysis of data science methods, using supplementary technical assignments in the Python Programming Language to teach:

(1) Basics of Python

(2) Reading in and examining datasets

(3) Performing data transformations

(4) Performing visualisations and mapping

(5) Working with categorical and text data

(6) Web scraping

(7) Application Programming Interfaces (APIs)

(8) Merging and joining datasets (and how to spot misinformation in political advertisements as a real-world social sciences application for practice)

(9) Social Networks

The workshop involves short, hands-on coding sprints followed by structured Socratic discussions that prompt participants to analyse the social and ethical implications of their technical work. This interactive approach ensures participants leave not only with new coding skills but with a social analysis framework for critically examining the design and implementation decisions of their code to develop responsibly in their own research.

This workshop is part of our Methods Fellowship programme, which develops and delivers innovative teaching in digital methods. You can read more about the and view the complete series of workshops here.

Our CDH Methods workshops have limited places and are prioritised for students and staff at the University of Cambridge. However, if space is available, we welcome all participants who want to learn and apply digital methods and use digital tools in their research.

This session may be of particular interest to:

• PhD students in the Arts, Humanities and Social Sciences
• Early Career Researchers in the Arts, Humanities and Social Sciences

If you have specific accessibility needs for this event, please get in touch. We will do our best to accommodate any requests.

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Host or Publisher Cambridge Digital Humanities