Requirements for Masters in Computer Science

36 credit requirment prior to Fall 2024

An MS student must complete 30 points or 36 credits with the concentration option of approved coursework satisfying requirements A, B, and C, below.

30 CREDIT OPTION

An MS student must complete 30 points of approved coursework with a cumulative grade point average (GPA) of 3.0.

21 credits must be taken as standard CS classroom-based courses.
An additional 6 credits in standard graduate CS, Math and Data Science classroom-based courses; independent study; or MS thesis (no external internships). Independent study and master’s thesis require DGS approval.
The remaining 3 credits may be any of the above, or may be: credits transferred from previous graduate study in Computer Science at another university; external internship; or relevant graduate courses in other departments at NYU. At most 3 credits of external internship may be taken. Relevant graduate courses and external internship require DGS approval.

A. An MS student must complete the three foundational courses listed below, and maintain an average of B- (2.667) or better GPA in all three foundational courses attempted.

An MS student will remain in good standing only if he or she maintains an average of B- (2.667) or better GPA in all three foundational courses attempted. If a student does not satisfy this requirement, the student will be placed on probation. The student will have until the end of the following semester to restore himself or herself to good standing or will be terminated from the program.

A full-time MSCS student must successfully complete at least one of the three foundational courses within the first three courses taken and must successfully complete all three foundational courses in their first year of study.

A part-time MSCS student must successfully complete a foundational course as the first course taken and must successfully complete all three foundational courses within the first six courses taken.

B. An MS student must pass one course in one of the following four designated application areas: computation for science and society; graphics; intelligent systems; and databases.

Computation for science and society includes courses on numerical methods and courses on applications of computation to the physical, biological, and social sciences.

Graphics includes courses on computer graphics, visualization, solid modelling, vision, multimedia, and animation.

Intelligent systems includes any course on artificial intelligence, machine learning, data mining, and natural language processing.

Database courses include databases, distributed computing, and data mining.

Some courses can be counted in either of two areas. For example a student taking Computer Vision can count it either as an AI course or as a Graphics course (but not both).

C. An MS student must complete a designated capstone course with a grade of B (3.0) or better. Alternatively, subject to the requirements below and prior approval of the DGS, the student may complete a master's thesis or advanced lab.

Capstone courses are determined by the DGS. They require substantial programming effort and draw on key technical areas covered by the MS program. Examples of capstone courses include Advanced Computer Graphics, Advanced Database Systems, and Compiler Construction. It is highly recommended that a capstone course should be taken after completing all three foundational courses. There is no limit to the number of capstone courses a student can take. The capstone course will still be counted as a capstone course no matter which semester it is taken as long as a student earns a B grade or higher in the course.

A student may instead choose to write a master's thesis if the following conditions are satisfied: the student has a cumulative GPA of 3.75 after six courses; the student has completed all three foundational courses with at least a B+ in each; the student has found a full-time faculty member to serve as a thesis advisor; and the student has received approval from the DGS.

MS thesis counts for six credits of master's coursework. The thesis must satisfy the following criteria: it must be original research or design/implementation; the work required must be equivalent to that of two regular MS courses; the thesis must result in a high-quality document of 30-50 pages or more; and the thesis must be read and approved by two full-time faculty members, one of whom is the advisor. At the discretion of the advisor and the DGS, the thesis may be published on the department web page.

An MS student must complete 36 points of approved coursework satisfying requirements A, B, and C, below.

36 credit option with concentration (must declare after first semester of study by April 1st (fall admits) or November 1st (spring admits))

An MS student must complete 36 points of approved coursework with a cumulative grade point average (GPA) of 3.0.

21 credits must be taken as standard CS classroom-based courses.
An additional 6 credits in standard graduate CS, Math and Data Science classroom-based courses; independent study; or MS thesis (no external internships). Independent study and master’s thesis require DGS approval.
The remaining 9 credits may be any of the above, or may be: credits transferred from previous graduate study in Computer Science at another university; external internship; or relevant graduate courses in other departments at NYU. At most 6 credits of external internship may be taken. Relevant graduate courses and external internship require DGS approval.

A. An MS student must complete the three foundational courses listed below, and maintain an average of B- (2.667) or better GPA in all three foundational courses attempted.

A part-time MSCS student must successfully complete a foundational course as the first course taken and must successfully complete all three foundational courses within the first six courses taken.

B. An MS student must complete four courses including the concentration capstone in either the AI concentration or the System/Security concentration:
Concentration Courses-ARTIFICIAL INTELLIGENCE (12 credits)

Artificial Intelligence, CSCI-GA 2560 or Machine Learning, CSCI-GA 2565 (3 credits)
Approved AI elective 3 credits (3 credits)
Approved AI elective 3 credits (3 credits)
AI Capstone course (B grade or higher) (3 credits)

Concentration Courses- SYSTEMS AND SECURITY (12 credits)

Systems and Security elective (3 credits)
Systems and Security elective (3 credits)
Systems and Security elective (3 credits)
Systems and Security Capstone course (B grade or higher) (3 credits)

C. An MS student must complete a designated concentration capstone course with a grade of B (3.0) or better. Alternatively, subject to the requirements below and prior approval of the DGS, the student may complete a master's thesis or advanced lab.

Capstone courses are determined by the DGS. They require substantial programming effort and draw on key technical areas covered by the MS program. It is highly recommended that a capstone course should be taken after completing all three foundational courses. There is no limit to the number of capstone courses a student can take. The capstone course will still be counted as a capstone course no matter which semester it is taken as long as a student earns a B grade or higher in the course.

A note about the MS THESIS for AI Concentration or Systems/Security Concentration

Thesis option available with approval but it will not replace the concentration capstone course. The concentration capstone course is required. The thesis will count as elective credit only (6 credits over two semesters)