Computer Science Master of science degree

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Overview

Computer graphics and visualization, data management, and intelligent systems are just a few topics you’ll explore while developing the skills to keep up in this ever-changing field.


The computer science masters is designed for students who have an undergraduate degree (or minor) in computer science, as well as those who have a strong background in a field in which computers are applied, such as engineering, science, or business. You’ll apply theoretical principles underlying computer science, ensuring you acquire the intellectual tools necessary to keep up-to-date in this rapidly evolving discipline. With focused course work in areas such as computer graphics and visualization, data management, distributed systems, intelligent systems, programming languages and tools, and security, you’ll be prepared for career advancement in a range of areas.

The program consists of a core curriculum, a diverse set of clusters, and many additional electives. The clusters provide students with the opportunity to obtain depth in a computer science discipline. The electives add the necessary breadth of knowledge required by industry. This combination prepares our graduates to engineer modern computing systems and contribute to all aspects of systems life cycles.

Clusters are offered in a variety of areas, including computer graphics and visualization, data management, distributed systems, intelligent systems, programming languages and tools, security, and theory. Certain pre-approved courses from other departments also may be counted toward the degree.

The program helps students prepare for academic and research careers in computer science or a related discipline. The program is designed for students who have an undergraduate major or minor in computer science as well as those who have a strong background in a field in which computers are applied.

Faculty members in the department are actively engaged in research in artificial intelligence, wireless networks, pattern recognition, computer vision, visualization, data management, combinatorics, and distributed computing systems. There are many opportunities for graduate students to participate in these activities toward thesis or project work and independent study.

Plan of study

The program consists of 30 credit hours of course work, which includes one core course, three courses in a cluster, four electives, and a thesis or project. For those choosing to complete a project in place of a thesis, students complete one additional elective. The degree is offered on a full- or part-time basis.

Full-time students take three or four courses per semester and may be able to complete the course work in three semesters. Full-time students who are required to take additional bridge courses may be able to complete the course work in four semesters.

Part-time students take one or two courses per semester and may be able to complete the course work in four to five semesters. The time required to complete a master’s project is one semester. To complete a master’s thesis, two semesters is typical. 

Clusters

Students select three cluster courses from the following areas:

The computer graphics and visualization cluster provides the technical foundations for graduate studies in computer graphics and image understanding. Areas for further study include graphics programming, rendering and image synthesis, computer animation and virtual reality, image processing, and analysis, and data visualization.

The data management cluster studies the foundational data management and knowledge discovery challenges prevalent in design, analysis, and organization of data. The courses cover general database issues including database design, database theory, data management, and data mining.

The distributed systems cluster studies systems formed from multiple cooperating computers, including the analysis, design, and implementation of distributed systems, distributed middleware, and computer networking protocols, including security.

Intelligent systems encompasses the study of algorithms and architectures that enable effective decision making in complex environments. Courses cover computer vision, robotics, virtual theater, sensor networks, data mining, document recognition, and the theoretical foundations of decision-making (e.g., Markov chains and the properties of voting protocols).

The languages and tools cluster combines language design and implementation together with architecture and the use of software development tools. Students specializing in this cluster gain a broad understanding of theoretical and applied knowledge.

The security cluster spans topics from networking to cryptography to secure databases. By choosing different domains in which to study security students gain a broad understanding of both theoretical and applied knowledge.

The theory cluster studies the fundamentals of computation, which includes complexity theory to determine the inherent limits of computation, communication, and cryptography and the design and analysis of algorithms to obtain optimal solutions within those limits.

Electives

Electives provide a breadth of experience in computer science and applications areas. Students who wish to include courses from departments outside of computer science need prior approval from the graduate program director. Refer to the course descriptions in the departments of computer science, engineering, mathematical sciences, and imaging science for possible elective courses.

Master's thesis/project

Students may choose the thesis or project option as the capstone to the program. Students who choose the project option must register for Computer Science MS Project (CSCI-788). Students participate in required in-class presentations that are critiqued. A summary project report and public presentation of the student's project (in poster form) occurs at the end of the semester.

Industries


  • Aerospace

  • Insurance

  • Government (Local, State, Federal)

  • Internet and Software

  • Defense

  • Electronic and Computer Hardware

  • Manufacturing

Typical Job Titles

Software Developer Software Engineer
Application Developer Programmer/Analyst
Database Administrator Security Engineer
System Integration Engineer

95%

outcome rate of graduates

$95k

median first-year salary of graduates

Latest News

  • June 4, 2019

    The NSF 2026 Idea Machine graphic with overhead view of round tables that look like gears.

    RIT a finalist in NSF 2026 Idea Machine competition

    The National Science Foundation received more than 800 idea submissions for the NSF 2026 Idea Machine competition. Entries were judged and 33 are still in the running for the grand prize, including a submission from an RIT team on Integrated Human Machine Intelligence.

  • April 23, 2019

    Three researchers sit at a desk on computers.

    RIT cyber fighters go deep on Tor security

    Recognizing that the internet is not always secure, millions of people are turning to the Tor anonymity system as a way to browse the World Wide Web more privately. However, Tor has been found to have its own vulnerabilities. This has a team of faculty and students from RIT’s Center for Cybersecurity researching the extent of the problem and ways to address it.

Curriculum

Computer Science (thesis option), MS degree, typical course sequence

Course Sem. Cr. Hrs.
CSCI-665
Foundations of Algorithms
This course provides an introduction to the design and analysis of algorithms. It covers a variety of classical algorithms and their complexity and will equip students with the intellectual tools to design, analyze, implement, and evaluate their own algorithms. Note: students who take CSCI-261 or CSCI-264 may not take CSCI-665 for credit.
3
CSCI-790
Computer Science MS Thesis
Thesis capstone of the master's degree program. Student must submit an acceptable thesis proposal in order to enroll. It is expected that the work would lead to a paper of the caliber of those generally acceptable to a national conference.
6
 
Cluster Courses
9
 
Electives
12
Total Semester Credit Hours
30

Computer Science (project option), MS degree, typical course sequence

Course Sem. Cr. Hrs.
CSCI-665
Foundations of Algorithms
This course provides an introduction to the design and analysis of algorithms. It covers a variety of classical algorithms and their complexity and will equip students with the intellectual tools to design, analyze, implement, and evaluate their own algorithms. Note: students who take CSCI-261 or CSCI-264 may not take CSCI-665 for credit.
3
CSCI-788
Computer Science MS Project
Project capstone of the master's degree program. Students select from a set of possible projects and confirm that they have a project adviser. Students enroll in a required colloquium component that meets weekly, during which they present information, related to their projects. Projects culminate with delivery of a final report and participation in a poster session open to the public.
3
 
Cluster Courses
9
 
Electives
15
Total Semester Credit Hours
30

Admission Requirements

To be considered for admission to the MS in computer science, candidates must fulfill the following requirements:

  • Complete a graduate application
  • Hold a baccalaureate degree (or equivalent) from an accredited university or college. 
  • Submit official transcripts (in English) of all previously completed undergraduate and graduate course work.
  • Have a minimum cumulative GPA of 3.0 (or equivalent). 
  • Submit scores from the GRE. Applicants with undergraduate degrees from foreign colleges and universities are required to submit GRE scores. GRE scores from other students may be requested.
  • Submit a personal statement of educational objectives outlining the applicant’s research/project interests, career goals, and suitability to the program.
  • Submit two letters of recommendation from academic or professional sources.
  • International applicants whose native language is not English must submit scores from the TOEFL, IELTS, or PTE. A minimum TOEFL score of 88 (internet-based) is required. A minimum IELTS score of 6.5 is required. The English language test score requirement is waived for native speakers of English or for those submitting transcripts from degrees earned at American institutions.

Prerequisites

Applicants must satisfy prerequisite requirements in mathematics (differential and integral calculus, probability and statistics, discrete mathematics, and computer science theory) and computing (experience with a modern high-level language [e.g., C++, Java], data structures, software design methodology, introductory computer architecture, operating systems, and programming language concepts).

Bridge courses

If an applicant lacks any prerequisites, bridge courses may be recommended to provide students with the required knowledge and skills needed for the program. If any bridge courses are indicated in a student's plan of study, the student may be admitted to the program on the condition that they successfully complete the recommended bridge courses with a grade of B (3.0) or better (courses with lower grades must be repeated). Generally, formal acceptance into the program is deferred until the applicant has made significant progress in this additional course work. Bridge program courses are not counted as part of the 30 credit hours required for the master's degree. During orientation, bridge exams are conducted. These exams are the equivalent to the finals of the bridge courses. Bridge courses will be waived if the exams are passed.

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Additional Info

Faculty

Faculty members in the department are actively engaged in research in the areas of artificial intelligence, computer networking, pattern recognition, computer vision, graphics, visualization, data management, theory, and distributed computing systems. There are many opportunities for graduate students to participate in these activities toward thesis or project work and independent study.

Maximum time limit

University policy requires that graduate programs be completed within seven years of the student's initial registration for courses in the program. Bridge courses are excluded.