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
Specializations
Software Development students will graduate prepared to design, develop, test and evaluate the software. Students are trained to be in charge of the design, development, testing, and evaluation of the 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.
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
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 - the remainder of credits
Completion in 24 months
- 6 - 9 credits taken each semester
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Computer Science M.S. Curriculum
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
or
- CISC 601 Software Development Project
or
- CISC 602 Data Science Project
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:
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
Admission Requirements
- Baccalaureate transcript
- 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 Structures
- 2 courses in Calculus
- At least 1 course in Data Structures
Linear Algebra and Analysis of Algorithms are recommended but not needed.