The employment landscape for computer science-related professions is strong. Technology generally (and computer science specifically) dominate the job market, in terms of necessary skills for success in virtually all career areas.
Students who enroll in the Computer Science graduate program will achieve knowledge and competency in the core areas of advanced database system design, compiler design, algorithms and theory of computation, software design and architecture, and distributed operating systems. Students will be able to choose from a variety of elective courses in mobile applications, cryptography, machine learning, and robotics; and they will select specializations in data mining and predictive analytics, software development, artificial intelligence, or cybersecurity.
Designed both for students with undergraduate degrees in computer science, as well as for career-changers. The method of delivery will mainly be as a campus-based program, with the option to expand to offer some courses as hybrid or online. The courses will be offered in the evening in Queens. Program delivery will accommodate full-time students in either 3 or 4 semesters as well as part time students.
The program supports the core Vincentian values of compassion and service in providing students with technical skills that can be used to combat poverty, disease, crime, as well as provide solutions in healthcare. It will utilize new instructional labs in St. Augustine Hall to provide maximum support for students' academic success.
- Degree Type
- MS
- Area of Interest
- Computing & Technology
- Associated Colleges or Schools
- Program Location
- Queens Campus
- Required Credit Hours
- 30
Contact Us
We are here to answer any questions you may have about the Computer Science program and admission process.
Justin Goldberg
Graduate Assistant Dean
ccpsgrad@stjohns.edu
Program Director
Christoforou Christoforos
Admission Requirements
All applicants must possess a bachelor’s degree from an accredited institution or the international equivalent before enrollment at the graduate level. In addition to the application form and non-refundable application fee, candidates should submit the following:
- Statement of professional goals and resume, which can be uploaded as part of the application for admission.
- Official transcripts from all undergraduate, graduate, and professional schools attended.
- One letter of recommendation obtained from a professional or academic reference.
- Completion of courses in Calculus I/II, Discrete Mathematics, Algorithms and Data Structures, Programming I/II; or at the division’s discretion.
- GRE Scores (optional but recommended): Applicants may submit an official copy of their GRE scores, in verbal reasoning, quantitative reasoning, and analytical writing, taken within 5 years of application in support of their application.
- Official TOEFL, IELTS, PTE or Duolingo scores are required for applicants whose native language is not English.
- Students with international credits must submit a course-by-course foreign credit evaluation with GPA calculation from a NACES member
Pre-Requisite Policy
Applicants who do not meet the minimum pre-requisites may be required to complete additional courses as non-matric students to fulfill these prerequisites before being admitted into the program. These pre-requisite courses will not apply to the M.S. degree.
For more information, please contact:
Office of Graduate Admission
718-990-1601
gradhelp@stjohns.edu
Degree Requirements
The M.S. degree program requires all students to complete 30 credits according to the following degree requirements. Students must:
- complete 5 core courses; equivalent to 15 credit units;
- complete 3 elective courses from one or more specialization areas; equivalent to 9 credit units;
- complete one of the degree-required options/concentrations (accounts for 6 credit units).
- Research option (requires the approval of a supervising professor): Students must enroll in CUS 795 and CUS 796 Master’s Thesis course, for two consecutive semesters and complete a master thesis report under the supervision of a faculty.
- Applied (non-thesis) option: Students must complete, CUS790 Master’s Capstone Project, plus one elective course from any of the specialization areas.
Specializations
The M.S. in computer science program elective courses are organized in specialization areas to allow students to tailor their degree to fit their academic and professional goals. Students, can elect to concentrate on a particular specialization by completing 3 elective courses within that specialization area. Current specializations include: Data Science Artificial Intelligence, Cybersecurity and Software Development.
Coursework Details
- CUS 715 Algorithms and Theory of Computation.
- CUS 720 Software Design and Architecture
- CUS 725 Advanced Database Management Systems
- CUS 730 Distributed Operating Systems
- CUS 610 Data Mining and Predictive Modeling I
- CUS 615 Data Mining and Predictive Modeling II
- CUS 635 Web Data Mining
- CUS 680 Distributed Big Data Analytics I
- CUS 681 Distributed Big Data Analytics II
- CUS 750 Robotics
- CUS 752 Machine Learning
- CUS 754 Computer Vision and Applications
- CUS 640 Natural Language Processing
- CUS 740 Software Testing and Quality Assurance
- CUS 742 Mobile Application Development
- CUS 744 Software Engineering
- CUS 746 Secure Software Development
Required PC Specs for Students
CPU: Intel or AMD CPU (2011 or later) - 64-bit x86/AMD64 CPU with a minimum of 4 cores. (CPUs with at least 6 to 12 cores are recommended). Newer Apple computers with Apple Silicon (e.g., M1, M2, M3, or Mx CPUs) are NOT supported and NOT compatible with the required software needed for this program.
System Memory: 16GB RAM (32GB or 64GB preferred).
System Storage: 512GB free space on internal SSD HD (1TB or greater preferred). External SSDs will NOT be supported.
Virtualization: Enabled in EUFI or BIOS (usually called VT-x or Intel Virtualization Technology for Intel-based CPUs; for AMD CPUs, it is often labeled as AMD-V or SVM (Secure Virtual Machine)).
Host Machine Operating Systems:
Windows 10 or 11
Windows Server 2012, 2016, or 2019
Ubuntu, Red Hat, Debian, Fedora, CentOS, Mint, or openSUSE Linux
MacOS 12, 13, or 14 - ONLY with a supported Intel-based CPU.
Admin Access: Full Admin access and control of the PC. Do NOT attempt to use a school/company/work-owned computer that is used in any Production or Development environment,
Licensed Software:
VMware Workstation Pro 17 or newer. Alternate hypervisors, such as Oracle Virtual Box or MS Hyper-V will NOT be supported.
VMware Fusion Pro 13 or newer - ONLY with a supported macOS AND Intel-based CPU
Unsupported CPUs:
Intel Atom processors based on the 2011 “Bonnell” micro-architecture (e.g., Atom Z670/Z650; Atom N570)
Systems using Intel Atom processors based on the 2012 “Saltwell” micro-architecture (e.g., Atom S1200, Atom D2700/D2500, Atom N2800/N2600).
Systems using AMD processors based on the “Llano” and “Bobcat” micro-architectures (e.g., code-named “Hondo”, “Ontario”, “Zacate”, “Llano”).
Supported CPUs:
Intel processors based on the 2010 “Westmere” micro-architecture (e.g., Xeon 5600, Xeon 3600, Core i7-970, Core i7-980, Core i7-990).
Career Outcomes
The 30-credit M.S. degree program in Computer Science combines foundational computer science with the advanced technical skills needed for today’s high-tech careers. The program aims to prepare students with the required qualifications to become Software Developers, Database Administrators, Data Analytics Specialists, Artificial Intelligence/Machine Lea Specialists, Artificial Intelligence/Machine Learning Specialists, Information Security Analysts, or to pursue further research or a doctoral degree in computer science.
