VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.
Building a Robot Judge: Data Science for Decision-Making (Course Project)
Last Updated: 2026-02-05 15:48:17
Abstract
Students investigate and implement the relevant machine learning tools for making legal predictions, including regression, classification, and deep neural networks models. This is the extra credit for a larger course project for the course.
Objective
In a semester paper, students (individually or in groups) will conceive and implement their own research project applying natural language tools to legal texts. Some programming experience in Python is required, and some experience with NLP is highly recommended.
Content
Students will investigate and implement the relevant machine learning tools for making legal predictions, including regression, classification, and deep neural networks models. We will use these predictions to better understand the operation of the legal system. In a semester project, student groups will conceive and implement a research design for examining this type of empirical research question.
General Information
- Language
- English
- Levels
- DS , DR , MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture |
Building a Robot Judge: Data Science for Decision-Making (Course Project)
Mondays, 12 - 2 pm. Same dates and room as for the lecture course 851-0760-00 V Building a Robot Judge: Data Science for Decision-Making.
|
No time listed | 28 h semesterly |
Offered In
-
GESS Science in Perspective (Only the topics listed in this paragraph can be chosen as GESS Science in Perspective. Further below you will find the "type B courses Reflections about subject specific methods and content" as well as the language courses. 6 ECTS need to be acquired during the BA and 2 ECTS during the MA Students who already took a course within their main study program are NOT allowed to take the course again.)
-
Type A: Enhancement of Reflection Competence (Suitable for all students. Students who already took a course within their main study program are NOT allowed to take the course again.)
-
Type B: Reflection About Subject-Specific Methods and Contents (Subject-specific courses: Recommended for doctoral, master and bachelor students (after first-year examination only). Students who already took a course within their main study program are NOT allowed to take the course again. These course units are also listed under "Type A", which basically means all students can enroll)
-
-
Doctoral Department of Humanities, Social and Political Sciences (More Information at: )
-