Repository for Big Data for Public Policy @ ETH Zurich, Spring 2023 (Syllabus)
Lecturers: Sergio Galletta, Elliott Ash, Christoph Goessmann
This course provides an introduction to data science and applied economics methods for policy applications. Students will put these techniques to work on a course project using real-world data, to be designed and implemented in consultation with the instructors.
Student presentations: Please choose a paper and sign up for a presentation slot in the presentation schedule with your group by 19 March (see the corresponding section of the syllabus). If you would like us to match you into a group with somebody else, please also let us know by the same date.
Student projects: Please choose a project and register it with us by 9 April here.
- Projects presentations are on 1 June.
- By 21 July you will have to hand in your paper/web app including the replication package. Please use this link to submit your project using the naming scheme
project_group_[#]_[app/paper].zip
.
# | Date | Lecture | Lecturer |
---|---|---|---|
01 | 23 February | Overview of the class | Galletta |
02 | 2 March | Working with (big) data I | Goessmann |
03 | 9 March | Applied Micro Methods I | Galletta |
04 | 16 March | Working with (big) data II | Goessmann |
05 | 23 March | Applied Micro Methods II | Galletta |
06 | 30 March | Machine Learning Intro | Goessmann |
07 | 6 April | Web Apps, SDG Monitor | Goessmann |
08 | 20 April | Supervised ML | Galletta |
09 | 27 April | Unsupervised ML | Galletta |
10 | 4 May | NLP | Ash |
11 | 11 May | Guest Lecture (Dean Knox - University of Pennsylvania) | Ash |
12 | 25 May | AI and Fairness | Galletta |
13 | 1 June | Project presentations, final lecture | Goessmann |