Artificial Intelligence Programming at Tufts
Tufts’ strength in computer science, engineering, and interdisciplinary learning, combined with their proximity to high-tech hubs such as Boston and Cambridge, make the School of Engineering an ideal environment for students interested in expanding their AI knowledge and career potential. This page details current AI programming and will be updated as new programs are added.
M.S. in Artificial Intelligence, Computer Science track
The MSAI – Computer Science track focuses on the principles and applications of machine learning and artificial intelligence from a computational perspective, with a strong emphasis on the broader social context in which AI technologies are developed and deployed.
This track requires one track-specific course, four AI breadth electives, and one general elective. As there are many possible paths through the program, the choice of electives is broad, and students will select appropriate electives with the advice of their advisor. The electives may include an additional ethics/social context course, if both the student and advisor feel that is appropriate.
M.S. in Artificial Intelligence, Electrical and Computer Engineering track
The MSAI – Electrical and Computer Engineering track integrates principles of machine learning and artificial general intelligence with specialized engineering domain knowledge, covering both fundamental and systems concepts in AI and how to apply these methods to diverse domains.
This track requires one track-specific course, four courses from theory/systems electives and two courses from domain-specific electives. The theory/systems track focuses on foundational and theoretical aspects that include basic concepts, techniques, algorithms and methods, and systems engineering concepts that aim to develop specialized hardware to efficiently run modern AI algorithms. The goal of the domain-specific elective track is to expose students to AI challenges across multiple disciplines.