Artificial Intelligence and Machine Learning

Information Introduction

LAW7127
Section 1, Spring 25

Schedule Information

Enrollment: /44
Credits: 3
Days Time Room Start Date End Date

Mon

,

Wed

1410-1530 WB105

Course Description

This course will consider artificial intelligence and machine learning from the perspective of law. Students will develop a basic understanding of the computer science underlying both artificial intelligence and machine learning, the ways in which the law is adapting (or failing to adapt) to artificial intelligence and machine learning, and the ways in which these technologies may be used by lawyers and legal researchers. Students need no background in computer science or coding.

Course Requirements

Exam Information

Description: None

Written Work Product

For the first part of the class, there will a combination of quizzes, projects, and a short writing assignment. For the second part of the class, students will write two or three two-page reading response papers (due directly to the instructor, not via EXPO), and a final, five-page paper on a topic of their choosing, subject to instructor approval. The final paper will be due via EXPO by noon on May 8, 2025.

Other Course Details

Prerequisites: None Concurrencies: None

Exclusive With: Law and Artificial Intelligence (7203)

Laptops Allowed: No

First Day Attendance Required: No

Course Resources: To be announced.

Graduation Requirements

Satisfies Understanding Bias/Racism/Cross-Cultural Competency requirement: No

Satisfies Writing Requirement: No

Credits For Prof. Skills Requirement: No

Satisfies Professional Ethics: No

Additional Course Information

Schedule No.: 125218846

Modified Type: Lecture

Cross Listed: No

Waitlist Count: 0

Concentrations: Law and Technology

Evaluation Portal Via LawWeb Opens: Sunday, April 13, 12:01 AM

Evaluation Portal Via LawWeb Closes: Sunday, April 27, 11:59 PM

Information reflected on this page was last refreshed at: Friday, July 19, 2024 - 7:02 AM *

*During open enrollment periods, live enrollment data may be found in SIS.