Master of Science in Computer Science

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Overview

The Master of Science in Computer Science (MSCS) program is designed to appeal to a broad range of individuals. The program balances theory with practice, offers an extensive set of traditional and state-of-the-art courses, and provides the necessary flexibility to accommodate students with various backgrounds, including computer professionals who want to expand their understanding of Computer Science, as well as individuals whose undergraduate degrees are not in Computer Science but wish to broaden their knowledge in computing. The program also provides the background necessary to continue the study of Computer Science at the doctoral level. Students may choose a thesis option, which requires two semesters of study under the direction of a professor in which the student gains an understanding of an area of current research and contributes to it.

PROGRAM OUTCOMES:

  • Apply object-oriented programming in desktop and mobile applications
  • Employ IDE and managerial tools in real world applications
  • Analyze current and future trends in computer science and adapt them appropriately to changing business needs
  • Illustrate effective communication and collaboration skills with stakeholders
  • Demonstrate understandings of privacy, security, forensics and copyright issues in professional and social environments
  • Understand various data structures and developing effective algorithms
  • Understand, develop and apply database management concepts and tools
  • Understand and design computer and network architecture and analyze different architectural models

SPECIALIZATIONS

Students choose an area and develop specialized knowledge in that area. Additionally, students work toward a project or research paper in their specialization, aimed at developing specific career-skills that they will use as they continue on into their professional trajectory. The following are offered as specializations in this program.

MS in Computer Science in Cybersecurity

The objective of this specialization is to equip the students with in-depth knowledge skills that will enable them to identify, develop, and implement effective and efficient defense mechanisms to secure organization networks and information resources to support organizational goals.

Career Paths

  • Chief Information Security Officer
  • IT Security Consultant
  • Digital Forensic Analyst

Related Microcredentials

These are mini-qualifications that demonstrate skills, knowledge, and/or experience in a given subject area or capability. The following are potential microcredentials in this area:

  • Chief Information Security Officer (CISO): Chief information security officer job emphasis on overseeing organizations network and data security, ensuring the security of an organization’s network and electronic documents, learning about new technology and look for ways to upgrade their organization’s computer systems, determining short- and long-term personnel needs for their department, planning and direct the work of other IT professionals, including computer systems analysts, software developers, information security analysts, and computer support specialists
  • IT Security Consultant: (ITSC): IT security consultant emphasis on securing IT, mentor staff and make sure the company meets its regulatory requirements, know how hackers work so the security consultant.
  • Digital Forensic Analyst: (DFA): Digital Forensic Analyst emphasis in looking to apply forensic skills and mindset to a critical mission assessing hardware and software platforms for potential security vulnerabilities, be familiar with commercial and open-source digital forensics tools, and think like the adversary and devise concise mitigation strategies to counter any and all threats in an effort to protect the platform and its users.

MS in Computer Science in Intelligent Systems

The objective of this specialization is to equip students with in-depth knowledge skills that will enable them to apply artificial intelligence (AI), machine learning and intelligent systems techniques to solve real-world problems.

Career Paths

  • Artificial Intelligence/Machine Learning Engineer
  • AI Specialist
  • AWS Machine Learning Engineer

Related Microcredentials

They are mini-qualifications that demonstrate skills, knowledge, and/or experience in a given subject area or capability.

  • Artificial Intelligence/Machine Learning Engineer (ALMLE): Demonstrated experience applying supervised and unsupervised techniques to structured data experience with at least one language for implementing AI/ML algorithms (e.g., Python, R). AIMLE leads software engineering teams in the architecture and implementation of solutions to solve challenging collaboration and social computing problems in domains such as healthcare, intelligence, and defense. AIMLE should be familiar with data management best practices and with DevOps patterns and practices.
  • AI Specialist (AISP): AISP work emphasize on analyzing massive data sets, leveraging modern DL frameworks to develop computer vision and Natural Language Processing (NLP) models. AISP uses statistical methods and leverage knowledge of large data sets to characterize uncertainty through statistical methods and analyze an Enterprise Analytics Platform (EAP) while working with a cross-functional team of data scientists, software engineers, and testers.
  • AWS Machine Learning Engineer (AWSMLE): AWSMLE work emphasizes on researching, innovating, and creating Prototypes and POCs for AI Platforms, tools & technologies to build models, deploy models into Production and monitor their performance. AWSMLE designs and develops software to extract, clean and manipulate large datasets both structured and unstructured. You will build and test the effectiveness and accuracy of Supervised and Unsupervised AI models including Image Analytics and NLP.

CURRICULUM OVERVIEW

The MSCS degree will be earned by completing the program course requirements of 36 credit hours, beyond the program prerequisite courses. To qualify for the MSCS degree, students must meet all credit requirements, as described below.

The MSCS program is generally completed within two years of full time study. It consists of five (5) required courses (15 credits), five (5) specialization courses (15 credits) and two (2) electives. The specialization courses allow a student to concentrate in a specific area for which there is demand and to achieve knowledge depth in that area. The two electives give a student the opportunity to integrate and apply the knowledge and skills studied so far to real-world situations/problems through a capstone project, internship or a master’s thesis. The specialization courses provide an opportunity for students to develop and fine-tune specific computing skills according to their areas of interest.

Area Number of Courses Credits
Required Courses 5 15
Specialization Courses 5 15
Elective Courses 2 6
Total 12 36
Required Courses

Each candidate must satisfactorily complete the following five (5) required courses (15 credits):

Code Course Name Prerequisite Credits
CMP 511 Computer Architecture and Implementation CMP 250 or CMP 260 3
CMP 556 Database Management Systems I CMP 350 3
CMP 560 Software Engineering None 3
CMP 561 Design and Analysis of Algorithms CMP 220 or CMP 330 3
CMP 641 Operating Systems CMP 260 3
Required Courses for each specialization:

Cybersecurity Courses

The objective of this specialization is to equip the students with in-depth knowledge skills that will enable them to identify, develop, and implement effective and efficient defense mechanisms to secure organization networks and information resources to support organizational goals.

Code Course Name Prerequisite Credits
CMP 558 Network and Information Security CMP 550/CMP 562 3
CMP 562 Computer Networks CMP 270 3
CMP 630 Network Security Audit and Forensics CMP 550 or CMP 562 3
CMP 643 Database Security and Data Protection CMP 556/CMP 553 3
CMP 644 Intrusion Detection and Prevention Systems CMP 558 3
CMP 645 Security Management CMP 558 3
CMP 647 Wireless and Mobile Security CMP 558 3
CMP 648 Special Topics in Cybersecurity Dean’s approval 3

Intelligent Systems Courses

The objective of this specialization is to equip students with in-depth knowledge skills that will enable them to apply artificial intelligence (AI), machine learning and intelligent systems techniques to solve real-world problems.

Code Course Name Prerequisite Credits
CMP 621 Artificial Intelligence None 3
CMP 652 Natural Language Processing CMP 561, CMP 621 3
CMP 653 Machine Learning CMP 621 3
CMP 654 Adaptive Learning Systems CMP 621 3
CMP 655 Intelligent Agents CMP 621 3
CMP 658 Special Topics Intelligent Systems Dean’s approval 3
Elective Course

The student must select two courses from the list of courses below or from any other specialization courses not already applied toward their degree. Students can only enroll in the Capstone project course of their chosen specialization.

Code Course Name Prerequisite Credits
CMP xxx Elective from any specialization Varies 3
CMP 551 Research Methods None 3
CMP 589 Computer Animation and Gaming Capstone Project All required courses, four specialization courses 3
CMP 609 Networking Capstone Project All required courses, four specialization courses 3
CMP 619 Software Applications Development Capstone Project All required courses, four specialization courses 3
CMP 629 Data Management Capstone Project All required courses, four specialization courses 3
CMP 639 Software Engineering Capstone Project All required courses, four specialization courses 3
CMP 649 Cybersecurity Capstone Project All required courses, four specialization courses 3
CMP 659 Intelligent Systems Capstone Project All required courses, four specialization courses 3
CMP 591 Graduate Internship Level I All required courses, four specialization courses, Dean’s approval 3
CMP 691 Graduate Internship Level II All required courses, four specialization courses, Dean’s approval 3
CMP 696 Independent Study I Dean’s approval 3
CMP 697 Independent Study II Dean’s approval 3
CMP 698 Master’s Thesis I All required courses, two specialization courses, academic advisor’s approval. 3
CMP 699 Master’s Thesis II CMP 698 3
CAR 600 Career Planning & Management None 3

NOTE: Students who wish to take a course that is offered by another graduate program outside of their major can petition to do so with permission from the instructor of the course and the Program Chair/Director. Requests are considered based upon a student’s previous academic performance including meeting the minimum attendance requirements for previous courses and maintaining satisfactory progress.

Master of Science in Computer Science Prerequisites

All new MSCS students need certain basic skills to prepare them for success in the MSCS program. The MSCS degree provides a broad understanding of computer science theory and technology. Students who do not have the required background need to take some or all the prerequisites before taking the Core Courses. In some cases, the program prerequisite courses may have course prerequisites to be taken before enrolling in the program prerequisite courses. Thus, to be successful, students must have a background in the following areas:

FXUA Course Related Course Subject(s) FXUA Course Description
CMP 220 Programming II Programming; Object Oriented Programming The course covers Object Oriented Programming OOP concepts for a selected OOP programming language. Topics include fundamental abstraction, modularity and encapsulation mechanisms in OOP, classes, inheritance, polymorphism, exception handling, concurrent programming, data structures. Students complete a term project that utilizes object-oriented programming.
CMP 260 Introduction to Operating Systems Operating Systems; Contemporary Operating Systems The course covers computer operating systems. Topics include concurrent processes and synchronization mechanisms; processor scheduling; memory management, virtual memory; paging, file management; input/output management; deadlock management; interrupt structures, interrupt processing; device management; performance of operating systems; synchronization in a multi-programmed operating system and with virtual memory management. Formal principles are illustrated with examples and case studies of one or more contemporary operating systems.
CMP 270 Essentials of Networking Essentials of Networking; Computer Networks and Internet The course covers computer networks and internet. Topics include network standards, concepts, topologies, and terminologies including LANs, WANs, Internet Protocol addressing, subnet masking and network design, and various protocols. This course teaches concepts from the Open Systems Interconnection (OSI) networking reference model, developed by the International Standards Organization to describe the function and structure of network communications protocols.
CMP 330 Data Structures and Algorithm Analysis Data Structures The course covers the analysis of algorithms and the effects of data structures on them. Topics include algorithms selected from areas such as sorting, searching, shortest paths, greedy algorithms, backtracking, divide and conquer, and dynamic programming. Data structures include heaps and search, splay, and spanning trees. Analysis techniques include asymptotic worst case, expected time, amortized analysis, solution of recurrence relation and reductions between problems.
CMP 350 Database concepts Database Design and Development The course covers fundamental concepts for design and development of database systems. Topics include review of relational data model and the relational manipulation languages SQL and QBE; integrity constraints; logical database design, dependency theory and normalization; query processing and optimization; transaction processing, concurrency control, recovery, and security issues in database systems; object-oriented and object-relational databases; distributed databases; emerging database applications.

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