Course Listing

Law and Data Science
Last Updated Date:   10 October 2024


5 Units,  Semester 2

Course Description:
This course offers a hands-on introduction to legal data science. With growing dependance on algorithmic, data-based and AI methods in law there is a growing necessity to critically examine these methods. Firstly, the course explores the use of different data sources that scholars and government officials use to make generalization, models and predictions in the realm of law. Secondly, the course introduces critiques of the use of predictive tools in the legal domain. Accordingly, the course contains readings and discussions which cover the use of data-based methods and prediction tools in the legal domain. Case studies and projects will enhance student understanding, providing them with the tools to critically analyize data based applications within legal contexts. By the end of the course, the students will be able to understand:

1. Complex legal issues that involve the use of data and prediction in law (such as for instance the growing use of prediction methods in criminal law such as risk assessment tools)
2. How data can be used in empirical legal research
3. The critique of the use of big data in sociolegal contexts.

Course Convenor: Mr Ilya Akdemir

Co-teacher(s): NA

Course Codes: LL4447V / LL5447V / LL6447V / LLJ5447V

Contact Hours: 3-hr weekly seminar

Workload: 3 hours

Mode of Assessment: Class participation - 15%; Homework Assignments (Essays on 4 readings) - 40% & Final Research Project - 45% [Due: Wednesday, 16 April 2025 (9am)]

Preclusions: LL4447/LL5447/LL6447/LLJ5447 Law and Data Science

Prerequisites: NUS Compulsory Core Law Curriculum or common law equivalent.
Basic programming skills in Python are required (for example, by taking the “Law and Technology” course).

Examination Date: Different Mode of Examination

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