Introduction to Probability and Statistics
Spring 2021/22, Winter 2022/23, Winter 2023/24
The first part of the course introduces basic concepts of probability theory: basic rules of probability, combinatory, conditional probability, discrete and continuous random variables and the central limit theorem. The second part focuses on statistical inference and includes descriptive statistics, sampling distribution, point estimation, confidence intervals, hypothesis testing, goodness of fit tests, tests of independence, and simple linear regression.
Game Theory and Economic Behavior
Spring 2021/22, Spring 2022/23, Winter 2023/24, Spring 2023/24, Winter 2024/25, Winter 2025/26
An introductory-level course on game theory and its applications in microeconomics. Topics covered:
1. One-stage games: dominated strategies, safety level strategies, Nash equilibrium and mixed strategies.
2. Zero-sum games and the minimax theorem.
3. Multi-stage games: subgame perfect equilibrium, backward induction and bargaining games.
4. Repeated games: punishment strategies and the folk theorem.
5. Games with incomplete information.
Learning Analytics (Data Science for Education)
Winter 2022/23, Spring 2022/23
This course is at the intersection of data science and social science. The course examines in depth the implications, challenges, potential, and concerns of using data to support learners. This course offers a snapshot of the field of learning analytics, focusing on both theory and practice. We will learn common approaches and main uses of learning analytics. We will also experiment with the analysis of data, and identify the potential of learning analytics to change the way we teach and learn. This version of the course focuses on the applications of artificial intelligence and data science to education: adaptive support in learning, assessment and classification of learners, identification of learning strategies and patterns from digital traces of learners, ethical implications of using data in education, and more.
Social Computing Models
Spring 2023/24, Spring 2024/25
This course explores the foundational principles of new interaction models within online social platforms, emphasizing both economic and algorithmic aspects. In particular, the course discusses the strategic and societal aspects of the following topics: the sharing economy, recommendation and ranking systems, influence in networks, algorithmic privacy and fairness, information design, and crypto-currency systems.