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  • M.S. in Computer Science

    Explore our M.S. in Computer Science
    Build a strong foundation and gain the skills you need to take your career to the next level.
    Degree:
    M.S.
    School:
    School of Liberal Arts
    Location:
    Dobbs Ferry, Bronx, Manhattan & Online
    Credits:
    30

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Computer Science M.S. Curriculum

Foundation Courses 9 Credits
Major Courses (based on area of specialization) 12 Credits
Two Electives 6 Credits
Capstone (Thesis/Project) 3 Credits
Total 30 Credits

Foundation Courses

  • CISC 505 Object Oriented Programming and Analysis of Algorithms
  • CISC 510 Theoretical Concepts in Computer Science
  • CISC 520 Database Management Systems

Major Courses

Specialization I: Software Development

  • CISC 515 Software Design and Development
  • CISC 545 Distributed Application Development
  • CISC 555 Mobile Application Development
  • CISC 575 Software Assurance

Specialization II: Data Science

  • CISC 530 Mathematical Models for Data Analysis
  • CISC 540 Computational Data Analysis
  • CISC 550 Machine Learning
  • CISC 560 Big Data

Electives

Any 2 courses from below:

  • CISC 565 (IASP 565) Social Media and Large-Scale Data Analytics
  • CISC 570 Advanced Operating Systems
  • Any other graduate CISC major course
  • Any graduate IASP (Cybersecurity) course

Capstone

  • CISC 600 Thesis
  • or
  • CISC 601 Software Development Project
  • or
  • CISC 602 Data Science Project
Does Mercy accept credits in transfer?
Yes, up to six credits in graduate Computer Science.
English isn't my native language. Is there an English language requirement?
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.
Is Mercy College a nonsectarian institution?
Yes. Qualified applicants are admitted without regard to race, religion, national or ethnic origin, gender, sexual orientation, marital status, age or physical disability.
Zhixiong Chen Professor, Cybersecurity
John Yoon Associate Professor, Cybersecurity
David Wang Associate Professor, Computer Science
Jon-Paul Paolino Assistant Professor, Mathematics
Narasimhaswamy Banavara Assistant Professor, Computer Information Systems
Sisi Li Assistant Professor

Computer Science Overview

The Master of Science (M.S.) degree in Computer Science (CS) provides an innovative curriculum involving two specializations – Software Development and Data Science. 

The M.S. in CS program is aimed to equip students with the necessary theoretical fundamentals as well as knowledge about cutting edge application tools to solve data science and software development problems

Computer Science Fast Facts

  • 30-credit program
  • Full-time students are able to finish the program in one year
  • Flexible offerings - on-campus, online or a hybrid of the two

Computer Science FAQS

Does Mercy accept credits in transfer?
Yes, up to six credits in graduate Computer Science.
English isn't my native language. Is there an English language requirement?
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.
Specializations

Software Development students will graduate prepared to design, develop, test and evaluate software. Students are trained to be in charge of the design, development, testing, and evaluation of software. 


Data Science students will acquire cutting-edge skills 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. 

Program Length
  • Completion in 12 months if taken on a full time basis
    • Year 1 - Fall - 12 credits
    • Year 1 - Spring - 12 credits
    • Year 1 - Summer - 1 - 6 credits
  • Completion in 18 months
    • Year 1 - Fall - 9-12 credits
    • Year 1 - Spring - 9 - 12 credits
    • Year 1 - Summer - 3 - 6 credits
    • Year 2 - Fall - remainder of credits
  • Completion in 24 months
    • 6 - 9 credits taken each semester

Admission Requirements

  • Baccalaureate transcrpt
    • GPA of 3.0 or higher
  • Curriculum Vitae
  • At least one letter of recommendation that provides evidence of personal and/or professional qualifications for graduate study.
Prerequisite Requirements
  • 1 course in Discrete Strucutres
  • 2 courses in Calculus
  • At least 1 course in Data Structures

Linear Algebra and Analysis of Algorithms are recommended but not needed.

Program Outcomes

For all students in the M.S. program in CS

Students who graduate with a Master’s in Computer Science should be able to:

  1. Communicate computer science concepts, designs, and solutions effectively and professionally
  2. Develop efficient and effective algorithmic solutions to real-world problems
  3. Analyze and evaluate the complexity and computability of solutions to real-world problems

For students in the Software Development specialization:

  1. Design, develop and test complex programs

For students in the Data Science specialization:

  1. Mine, analyze, and visualize data
  2. Solve real-world problems by applying principles of computing intelligence and data analytics
Program Goals

For all students in the M.S. program in CS:For all students in the M.S. program in CS:

  1. Acquire a working knowledge of the theoretical foundations of Computer Science
  2. Develop critical thinking, problem-solving and analytical skills

For students in the Software Development specialization:

  1. Develop software design and development skills

For students in the Data Science specialization:

  1. Develop an in-depth understanding of the key technologies in computer science and data science