Machine Learning for Social Sciences

Schedule: 22-23 July, 2025 (09.30-15.30 Jakarta Time)

About

In this course, we will learn fundamental techniques of machine learning that could be applied in social science context. There will be four sessions where each session will start with theoretical concepts and followed by hands-on coding experiments. Students are expected to install any working Python version with Anaconda run in Jupyter Lab in any IDE of their choice (I would suggest VS Code).

We plan to cover:
1. Basic data analytics using Python
2. Supervised Learning (regression, classification)
3. Unsupervised Learning (clustering, PCA)
4. Working with other data (text and images)

Instructor

Muhammad Al Atiqi

Affiliation: Universitas Islam Internasional Indonesia and Former Data Scientist Bukalapak

Muhammad Al Atiqi is a lecturer in the MPP program at UIII. He received his Ph.D. in artificial intelligence from the School of Computing at Tokyo Institute of Technology, after completing his M.Sc. in the same program and a B.Sc. in physics from Nanyang Technological University. Prior to joining UIII, he worked as a data scientist at tech companies in Indonesia and Japan. His research primarily revolves around computational social science, utilizing agent-based modeling and simulation methods. His research topics include, but are not limited to, public opinion formation modeling and bottom-up decision-making for various social policies.