Computer Science and Engineering Department
Program Description
We offer a highly adaptive MS in Computer Science program that lets students shape the degree around their interests. Besides our core curriculum in the fundamentals of computer science, students have a wealth of electives to choose from. Students can tailor their degree to their 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. Our graduates are prepared to 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 MS program in Computer Science, students will have significant curriculum flexibility, allowing them to adapt their program to their ambitions and goals as well as to their educational and professional background. Students will gain a solid grounding in the fundamentals of computer science, along with access to professional-level courses, and an opportunity to specialize in subareas of their choice.
Admissions
To apply for admission to any Tandon graduate program, please contact the Office of Graduate Admissions.
Required Background Knowledge
Admission to this program requires applicants 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 may also be considered 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. 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.
A maximum of 9 credits from previous graduate work at an accredited institution may be transferred to the MS degree.
Students with an undergraduate background in a field outside of computer science or a related area of study are encouraged to enroll into the preparatory NYU Tandon Bridge program. Upon successfully completing the Bridge program, students could then be considered for admission to the master's.
GRE Requirements
Applicants who satisfy one of the following conditions are not required but encouraged to submit a GRE score:
- MS 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 BA or BS degree in computer science or computer engineering from NYU, with a GPA of 3.0 or higher.
Program Requirements
Note: not all courses are offered every semester.
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 | |
CS-GY 6133 | | |
| 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 | |
CS-GY 6243 | | |
CS-GY 6253 | | |
CS-GY 6413 | | |
| Big Data | |
| Interactive Computer Graphics | |
| Penetration Testing and Vulnerability Analysis | |
| Artificial Intelligence I | |
| COMPUTER VISION | |
| Network Security | |
| Artificial Intelligence for Games | |
| Application Security | |
| | |
| MS THESIS IN COMPUTER SCIENCE | |
| 6 |
| 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 | |
CS-GY 6093 | | |
CS-GY 6133 | | |
| Introduction to Operating Systems | |
CS-GY 6243 | | |
CS-GY 6253 | | |
| INFORMATION VISUALIZATION | |
| LARGE-SCALE VISUAL ANALYTICS | |
| Programming Languages | |
CS-GY 6413 | | |
| 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 | |
| | |
| Application Security | |
| | |
| ADVANCED PROJECT IN COMPUTER SCIENCE | |
| MS THESIS IN COMPUTER SCIENCE | |
3 | 6 |
Total Credits | 30 |
GPA Requirements
The MS in Computer Science has several specific GPA requirements. 1. Core GPA: A core GPA of 3.0 or higher is required in the algorithms and core courses. The core GPA is calculated based on the grades earned in these five courses. 2. Capstone GPA: A GPA of 3.0 or higher is required in the capstone course. This is achieved by earning a grade of B or higher in the capstone course. 3. Cumulative GPA: A cumulative GPA (overall GPA) of 3.0 or higher is required in all graduate courses taken.
Capstone and Core Option
Some core courses may also count as capstone courses. These are those courses that appear on both the core and capstone lists above. Students may choose to use a core course to also satisfy the capstone requirement, if the grade earned in the course is B or higher. If the student chooses this option, the student must then take an additional computer science elective, so that the student may earn the required 30 credits needed for the MS degree. All students must earn 30 credits to graduate.
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 6083 |
Principles of Database Systems () |
3 |
CS-GY 6373 |
Programming Languages () |
3 |
| Credits | 9 |
2nd Semester/Term |
CS-GY 6033 |
Design and Analysis of Algorithms I () |
3 |
CS-GY 6643 |
COMPUTER VISION () |
3 |
| |
3 |
| Credits | 9 |
3rd Semester/Term |
CS-GY 6063 |
Software Engineering I () |
3 |
CS-GY 6513 |
Big Data () |
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 6083 |
Principles of Database Systems () |
3 |
CS-GY 6373 |
Programming Languages () |
3 |
| Credits | 9 |
2nd Semester/Term |
CS-GY 6063 |
Software Engineering I () |
3 |
CS-GY 6643 |
COMPUTER VISION () |
3 |
| |
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 |
CS-GY 6923 |
Machine Learning () |
3 |
| |
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.