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Program Description
We offer a highly adaptive M.S. in Computer Science program that lets you shape the degree around your interests. Besides our core curriculum in the fundamentals of computer science, you have a wealth of electives to choose from. You can tailor your degree to your professional goals and interests in areas such as cybersecurity, data science, information visualization, machine learning and AI, graphics, game engineering, responsible computing, algorithms, and web search technology.
Job opportunities in computer science are challenging and diverse, and we expect to see steady demand for highly qualified graduates at all levels. As a graduate, you can explore careers in areas such as applications programming, big data, software engineering, game design and programming, peer-to-peer networks, computer vision and imaging, machine learning and AI, urban computing, and interactive data visualization.
With our M.S. program in Computer Science, you will have significant curriculum flexibility, allowing you to adapt your program to your ambitions and goals as well as to your educational and professional background. You will gain a solid grounding in the fundamentals of computer science, along with access to professional-level courses, and an opportunity to specialize in selected technology areas of your choice.
Admissions
Admission to this program requires you to have an undergraduate degree in computer science, mathematics, science, or engineering, with a superior undergraduate record from an accredited institution. Applicants with degrees in other fields are considered individually for admission.
Additional Entrance Requirements
- At least 1 year of university-level science.
- A working knowledge of a high-level, general-purpose programming language (preferably C++).
- A basic understanding of computer fundamentals such as computer organization and operation, data structures, and computer architecture.
- Demonstrated ability to communicate in written and spoken English is required for regular status (see below). Foreign students and others for whom English is a second language may be required to undertake preparatory work to improve their language skills.
Students entering with a bachelor’s in computer science or with a bachelor’s in a technical area and a strong minor in computer science should be able to satisfy entrance requirements for the master’s degree program. Generally, entering students are expected to know mathematics through calculus.
Admission with advanced standing is accepted in accordance with the School of Engineering regulations. A maximum of 9 credits may be applied to the M.S. degree from previous graduate work at an acceptable institution.
Students who are lacking the computer science skills needed for the Computer Science Master's Degree are encouraged to enroll into the preparatory Bridge to NYU Tandon program. Pending satisfactory completion, students would be considered for admission towards the master's degree program.
GRE Requirements
Applicants who satisfy one of the following conditions are not required but encouraged to submit a GRE score:
- M.S. Applicants without a Computer Science or similar background who successfully complete the NYU Tandon Bridge.
- Applicant completes 9 credits under Visiting Student Registration from an approved list of CSE courses and maintains an average grade of B+ or better.
- Applicant has a B.A. or B.S. degree in computer science or computer engineering from NYU, with a GPA of 3.0 or higher.
Program Requirements
To satisfy the requirements for the master’s degree, the student must complete 30 credits, as described below, with an overall average of B. In addition, a B average is required across the required algorithms course and the four core courses, and a grade of B or better is required for the capstone course, as indicated below. The master’s curriculum has four components: 3 credits of algorithms, 12 credits of core elective courses (one of which may also count as the capstone course), one 3 credit capstone course, and 12 credits of general elective courses.
For students who enroll in the program with full-time status, the M.S. program is designed to be a 2-year program. Since not all courses are offered every semester, your course options are likely to be more limited if you elect to finish the program in less than 2 years.
Course List
Course |
Title |
Credits |
CS-GY 6033 | Design and Analysis of Algorithms I 1 | 3 |
or CS-GY 6043 | Design and Analysis of Algorithms II |
2 | 12 |
| Software Engineering I | |
| Principles of Database Systems | |
| Computer Architecture I | |
| Introduction to Operating Systems | |
| INFORMATION VISUALIZATION | |
| Programming Languages | |
| Big Data | |
| Interactive Computer Graphics | |
| Artificial Intelligence I | |
| COMPUTER VISION | |
| ALGORITHMIC MACHINE LEARNING AND DATA SCIENCE | |
| Information, Security and Privacy | |
| Computer Networking | |
| Machine Learning | |
3 | 3 |
| Foundation of Data Science | |
| Software Engineering I | |
| Operating Systems II | |
| Distributed Operating Systems | |
| Compiler Design and Construction | |
| Big Data | |
| Interactive Computer Graphics | |
| Penetration Testing and Vulnerability Analysis | |
| Artificial Intelligence I | |
| COMPUTER VISION | |
| Network Security | |
| Artificial Intelligence for Games | |
| Application Security | |
CS-GY 9223 | | |
4 | 12 |
| Foundations of Computer Science | |
| Design and Analysis of Algorithms I | |
| Design and Analysis of Algorithms II | |
| Foundation of Data Science | |
| Software Engineering I | |
| Principles of Database Systems | |
| Advanced Database Systems | |
| Computer Architecture I | |
| Introduction to Operating Systems | |
| Operating Systems II | |
| Distributed Operating Systems | |
| INFORMATION VISUALIZATION | |
| LARGE-SCALE VISUAL ANALYTICS | |
| Programming Languages | |
| Compiler Design and Construction | |
| Big Data | |
| Interactive Computer Graphics | |
| Human Computer Interaction | |
| Game Design | |
| Penetration Testing and Vulnerability Analysis | |
| Artificial Intelligence I | |
| COMPUTER VISION | |
| Computational Geometry | |
| Theory of Computation | |
| ALGORITHMIC MACHINE LEARNING AND DATA SCIENCE | |
| Information Systems Security Engineering and Management | |
| Information, Security and Privacy | |
| Network Security | |
| Computer Networking | |
| Applied Cryptography | |
| Web Search Engines | |
| Machine Learning | |
| Artificial Intelligence for Games | |
| DEEP LEARNING | |
| Digital Forensics | |
CS-GY 9053 | | |
| Application Security | |
CS-GY 9223 | | |
| ADVANCED PROJECT IN COMPUTER SCIENCE | |
| MS THESIS IN COMPUTER SCIENCE | |
Total Credits | 30 |
Sample Plan of Study
The particular courses that a student takes during the program will vary according to the student’s interests and background, course offerings, and whether the student does an internship. The following are two sample courses of study. These are just samples meant to help in planning the courses for the degree. Individual course plans may differ depending on when courses are offered.
Non-Internship Plan
Sample course plan for a student not doing an internship and taking CS-GY 6003 Foundations of Computer Science.
Plan of Study Grid
1st Semester/Term |
CS-GY 6003 |
Foundations of Computer Science |
3 |
CS-GY 6373 |
Programming Languages () |
3 |
CS-GY 6083 |
Principles of Database Systems () |
3 |
| Credits | 9 |
2nd Semester/Term |
CS-GY 6033 |
Design and Analysis of Algorithms I () |
3 |
|
3 |
CS-GY 6643 |
COMPUTER VISION () |
3 |
| Credits | 9 |
3rd Semester/Term |
CS-GY 6513 |
Big Data () |
3 |
CS-GY 6063 |
Software Engineering I () |
3 |
CS-GY 6923 |
Machine Learning () |
3 |
| Credits | 9 |
4th Semester/Term |
CS-GY 6813 |
Information, Security and Privacy () |
3 |
| Credits | 3 |
| Total Credits | 30 |
Internship Plan
Sample course plan for a student doing internships and not taking CS-GY 6003 Foundations of Computer Science.
Plan of Study Grid
1st Semester/Term |
CS-GY 6033 |
Design and Analysis of Algorithms I () |
3 |
CS-GY 6373 |
Programming Languages () |
3 |
CS-GY 6083 |
Principles of Database Systems () |
3 |
| Credits | 9 |
2nd Semester/Term |
CS-GY 6063 |
Software Engineering I () |
3 |
|
3 |
CS-GY 6643 |
COMPUTER VISION () |
3 |
| Credits | 9 |
3rd Semester/Term |
CP-GY 9911 |
Internship for MS I () |
1.5 |
| Credits | 1.5 |
4th Semester/Term |
CS-GY 6513 |
Big Data () |
3 |
|
3 |
CS-GY 6923 |
Machine Learning () |
3 |
| Credits | 9 |
5th Semester/Term |
CP-GY 9921 |
Internship for MS II () |
1.5 |
| Credits | 1.5 |
| Total Credits | 30 |
Learning Outcomes
Upon successful completion of the program, graduates will:
- Develop laboratory software skills for graduate level work.
- Learn advanced fundamentals in computer systems.
- Learn advanced fundamentals in computer science theory.
- Learn advanced fundamentals in software/programming.
- Broaden their backgrounds by taking important electives to further their special interest knowledge.
Policies
NYU Policies
University-wide policies can be found on the New York University Policy pages.
Tandon Policies
Additional academic policies can be found on the Tandon academic policy page.