Computer Science M.S.
- 30 - 36 Credits
- School of Liberal Arts
- Bronx
- Manhattan
- Online
- Westchester
Computer Science Overview
The Computer Science Master of Science degree equips students with cutting edge knowledge and tools to solve data science and software development problems. The program starts by providing fundamental computer science theories that make skilled practice possible.
Choose from specializations in data science, software development, or artificial intelligence and machine learning to pursue a career that best fits your interests. Solve some of the world's most interesting and challenging problems as you advance in your field.
Career Opportunities
Students can pursue careers as:
- Chief Information Officers
- Chief Technology Officers
- Data Scientists
- Computer and Information Research Scientists
- Mobile Application Developers
- Software Developers
- Web Developers
- AI Application Developers
- Computer Systems Analysts
- Security Analysts
- Database Administrators
And many more options
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Join us for an upcoming graduate admissions event to learn more about our Computer Science program and explore how ÃÍÄÐÇ鱨¾Ö can help you meet your goals.
The ÃÍÄÐÇ鱨¾Ö Advantage
- Take courses on-campus, online or a hybrid of the two
- The program is offered fully online
- Full-time or part-time enrollment
- ÃÍÄÐÇ鱨¾Ö offers rolling admissions for this program
Specializations
Software Development
In the Software Development specialization, students are introduced to and trained in the software design and development processes, including mobile and distributed data development, and software assurance. 
Students will graduate prepared to design, develop, test, and evaluate both simple and complex software.
30 credits
Data Science
In the Data Science specialization, students are introduced to and trained in the mathematical methods of data science, computational data analysis, machine learning, deep learning, and applications in big data. 
Across industries organizations are increasingly relying on data to make decisions. To manage all this data requires expertise not only in machine learning but also programming for data science and computing methods for big data.
30 credits
Artificial Intelligence and Machine Learning
In the Artificial Intelligence and Machine Learning specialization, students are introduced to and trained in the mathematical methods of data science, computational data analysis, machine learning and deep learning, artificial intelligence, computer vision, natural language processing, applications in big data, DevOps and ML-Ops, and data engineering services in the cloud. 
36 credits
Application Requirements
- Bachelor’s Degree - GPA of 3.0 or higher. If a student has a GPA less than 3.0 but greater than 2.5, the applicant must request an interview with the Program Director.
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- Statement of Purpose - Applicants must write an essay describing why they want to pursue the M.S. in Computer Science and what their career plans are after they graduate from the program.
- Letter of Recommendation – Applicants must submit at least one letter of recommendation from an individual qualified to assess their academic or professional qualifications for graduate study.
Bridge Program
ÃÍÄÐÇ鱨¾Ö has partnered with the NYU Tandon Bridge Program to provide students without a background in science or computer-related fields a path toward earning their M.S. in Cybersecurity or M.S. in Computer Science degree.
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Frequently Asked Questions
Qualifications
Applicants must demonstrate foundational knowledge in computer science, which includes proficiency in any programming language, as well as an understanding of operating systems and computer networks.
Prerequisites
Prerequisites are deemed fulfilled under the following conditions:
- The candidate holds a GPA of 3.0 or higher on a 4.0 scale.
- The candidate has earned an undergraduate degree in one of the following fields: Computer Science (CS), Cybersecurity (CSEC), Computer Information Systems (CIS), Information Science (IS), Information Technology (IT), Computer Networking (CN), Computer Engineering (CE), Electrical and Computer Engineering (ECE), Electrical Engineering (EE), or a related program that covers the aforementioned courses.
Candidates whose degrees are not in the specified majors but who can demonstrate mastery of the foundational knowledge may also be considered. Acceptable proofs of competence include:
- A certificate from the NYU Tandon Bridge program for non-STEM majors.
- Verified coursework from accredited institutions such as universities, colleges, or community colleges.
- Certificates from recognized online platforms like Coursera or EDX, subject to evaluation.
Program can be completed full-time in one year or part-time in two years.
Yes, faculty are always ready to help students with questions about what courses to take, the sequencing of courses, and career opportunities, including internships and cooperative education.
Yes, some evenings and weekends at the Dobbs Ferry and Bronx campuses.
You must demonstrate proficiency in English. That means reading, writing, speaking and an understanding of the spoken language at a graduate level. Proficiency will be determined by a Test of English as a Foreign Language (TOEFL) or a test(s) approved by the Dean of Graduate Studies.
Program Details & Curriculum
Foundation Courses: 9 Credits
Major Courses (based on area of specialization): 12 credits
Two Electives: 6 credits
Capstone: 3 credits
Total: 30 Credits
For all students in the M.S. program in Computer Science:
Students who graduate with a Master’s in Computer Science should be able to:
- Communicate computer science concepts, designs, and solutions effectively and professionally
- Develop efficient and effective algorithmic solutions to real-world problems
- Analyze and evaluate the complexity and computability of solutions to real-world problems
For students in the Software Development specialization:
- Design, develop and test complex programs
For students in the Data Science specialization:
- Mine, analyze, and visualize data
- Solve real-world problems by applying principles of computing intelligence and data analytics
Full-Time Faculty
Narasimhaswamy A Banavara
- GMH 113
- NBanavara@mercy.edu
- (914) 674-7443
David Wang
- GMH 109
- dwang@mercy.edu
Part-Time Faculty
