Overview of Course Offerings in Legal Data Science
Law and Statistics: Introduction to Quantitative Methods for Lawyers
Lecture, every Fall Semester
Target group: Bachelor students
Language: German
Description: At a time when more and more legal decisions and political measures are based on empirical data, an understanding of statistics is indispensable for lawyers. Statistical analysis provides tools - often under-appreciated and sometimes misapplied - to uncover discrimination in legal practice, evaluate the effectiveness of laws, or make predictions about court decisions and risks in legal proceedings. The course covers basic concepts of statistics such as descriptive analysis and probability as well as methods such as regression analysis and hypothesis testing. Wherever possible, legal cases from practice will be used to introduce statistical concepts. While the lecture “Introduction to Empirical Legal Studies” (now to be offered as a Master's lecture) aims to enable students to carry out their own data analyses (in the statistics program R), the lecture “Law and Statistics” is primarily aimed at developing a conceptual-theoretical understanding of the connection between law and statistics. Simple calculations are carried out using a pocket calculator. An introduction to R is not given.
The lecture is intended in particular as an introductory lecture in quantitative methods to lay the foundation for later deepening and expansion (e.g. in the Legal Tech lecture, the lecture “Introduction to Empirical Legal Studies”, “Introduction to Programming and Computational Thinking for Lawyers”).
Seminar: Empirical Analysis of the Law: A Challenge-Based Approach Using R
Seminar, every Fall Semester
Target group: Bachelor/Master students
Language: English
Description: The aim of this seminar is to provide law students with a basic understanding of the empirical legal research progress - from conceptualization, through data collection and analysis, to reporting. Students will work collaboratively in small groups to conceptualize and implement a small empirical research project using basic statistical methods in R. Learning objectives include the ability to employ simple quantitative methods in the legal field using the approproate software and the knowledge on how to plan and carry out entry-level empirical research projects.
Introduction to Programming and Computational Thinking for Lawyers
Lecture, every Fall Semester (not in Fall Semester 2025)
Target group: Bachelor students
Language: English
Description: This course is an introduction to programming especially designed for law students, where students will learn fundamental concepts and skills of programming that are relevant in legal contexts. Students will learn the syntax, control flow, data structures and file input/output in Python and will also gain an understanding of how algorithms and computational thinking are used in computer science, as well as how computational methods and tools can be used by lawyers.
Instructor: Prof. Dr. Alberto Bacchelli (UZH Department of Informatics)
Online Course II: Legal Data Science
Online course, every semester beginning in the Fall Semester 2023
Target group: Master/Doctoral students
Language: English
Description: This course aims to introduce students to legal data science and teach them competences in R and statistics. Students will for example learn how to analyze and visualize data using datasets with a legal context. The course is designed for law students who are interested in expanding their skillset to data science and intend to use these skills to conduct simple legal data science projects, for example as part of their master thesis or dissertation.