Repository for Data Science for Public Policy: From Econometrics to AI @ ETH Zurich, Spring 2024 (Syllabus)
Lecturers: Sergio Galletta, Elliott Ash, Christoph Goessmann
This course provides an introduction to data science, AI, 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.
Please choose a paper and sign up for a presentation slot in the presentation schedule with your group by 11 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.
Upload your paper presentation here by 6 June using the naming scheme paper_group_[##]_presentation.[pdf/pptx/key/txt]
.
Please choose a project and register it with us by 16 April here (be sure to go to the course project sheet, feel free to open an new discussion here to pitch your course project idea to others).
- Projects presentations – 4 minutes per group – are on 30 May.
- Upload here by 10 am the same day using the naming scheme
project_group_[##]_presentation.[pdf/pptx/key/txt]
. We will prepare a laptop with all the presentations so that we waste little time between groups. - Potential structure:
- What are you trying to do and why is it relevant?
- How are you doing it (methods)?
- What are your preliminary results?
- What are your pain points?
- Upload here by 10 am the same day using the naming scheme
- 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 | 22 February | Overview | Galletta |
02 | 29 February | Working with (Big) Data I | Goessmann |
03 | 7 March | Applied Micro Methods I | Galletta |
04 | 14 March | Working with (Big) Data II | Goessmann |
05 | 21 March | Applied Micro Methods II | Galletta |
06 | 28 March | Machine Learning Intro | Goessmann |
07 | 11 April | NLP I | Ash |
08 | 18 April | Supervised ML | Galletta |
09 | 25 April | Unsupervised ML | Galletta |
10 | 16 May | Web Apps (e.g., SDG Monitor) | Goessmann |
11 | 23 May | AI and Fairness | Galletta |
12 | VIDEO | NLP II | Ash |
13 | 30 May | Project Presentations, final lecture | Goessmann |