The program's course requirements are designed to provide students with a shared introduction to basic tools of philosophical analysis, a shared background of philosophical issues, significant interdisciplinary competence, and an introduction to research topics in the department.
By default students are presumed to be in the course-based degree option (they will not write a thesis). If a student would like to write a thesis, they must seek approval from one member of the department (the supervisor) and one additional faculty member (the second reader). This permission must be secured prior to the first day of classes of the fourth semester, but students are strongly advised to secure it earlier.
In the requirements below we refer to the "philosophical areas."
For the purpose of our requirements, philosophical areas are:
- Area 1: Philosophy of Science, Methodology, and Epistemology
- Area 2: Value Theory
- Area 3: History of Philosophy
- Area 4: Philosophy of Mind, Philosophy of Language, Lingusitics, and Metaphysics
- Area 5: Philosophy of Mathematics and Logic
- 80-600 Philosophy Core Seminar I and II (2 semesters): Survey of crucial research in philosophy, logic, and related areas
- 80-610 Formal Logic: The syntax and semantics of first-order logic, and related topics
- 80-618 Topics in Logic I (half semester): The theory of computability, and Gödel's incompleteness theorems
- 80-616 Formal Methods (1.5 semesters): An introduction to contemporary formal frameworks, including Bayes Nets, Decision Theory, Game Theory, and Formal Learning Theory
- Professional development seminar: Students must enroll in the professional development seminar in the spring semester of both years
- Two courses from two different philosophical areas
- Two graduate level courses from any of the five philosophical areas
- Two course of independent thesis research
An interdisciplinary elective, e.g. in logic, computer science, statistics, game theory, linguistics, economics, or psychology, to develop formal skills that will support thesis research. These courses need to be approved by the Director of Graduate Studies. Suitable courses include:
- 10-701 Machine Learning
- 15-211 Fundamental Data Structures and Algorithms
- 21-601 Model Theory I
- 36-625 Probability and Mathematical Statistics I
- 85-719 Introduction to Parallel Distributed Processing
- 85-765 Cognitive Neuroscience
- Two additional graduate level courses
NOTE: A maximum of two directed readings may be used to fulfill the requirements for the course-based masters degree without special permission from the Director of Graduate Studies. Students in the course-based option are encouraged, however, to consider taking at least one directed reading to further delve into an area of a previous course.