Master’s in Computer Science Online Curriculum
Each one of Bradley University’s online Master of Science (M.S.) in Computer Science courses is designed and taught by our accomplished, dedicated faculty. Through a mix of core courses and electives, you’ll gain mastery of several computer science theories and skills, such as software engineering, computing, and data science.
Required Core Courses
CS 514 - Algorithms (3 hours)
Design and analysis of algorithms. Dynamic structures maintenance and hashing. Searching, sorting, and traversal. Time and space requirements; simplification; computational complexity; proof theory and testing; NP-hard and NP-complete problems.
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 210 or CIS 210 or equivalent and one semester of statistics.
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 210 or CIS 210 or equivalent and one semester of statistics.
CS 520 - Advanced Computer Architecture (3 hours)
Fundamental computer subsystems: central processing unit; memory systems; control and input/output units. General purpose computing systems design. Examples from existing typical computers.
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 220 or equivalent.
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 220 or equivalent.
CS 571 - Database Management Systems (3 hours)
Relational database design, including entity relationship modeling and normalization. Structured query language (SQL) for creating and querying databases. Other topics include the theory of relational databases, including relational algebra, various loading and reporting utilities, and the implementation of database management systems, e.g., how query optimization works.
Prerequisite: Graduate standing in CS or CIS or Data Science and Analytics who have taken CS 541 or two semesters of computer programming.
Prerequisite: Graduate standing in CS or CIS or Data Science and Analytics who have taken CS 541 or two semesters of computer programming.
CS 590 - Fundamentals of Software Engineering (3 hours)
Software engineering: software product; prescriptive process models; system engineering; analysis modeling; design engineering; architectural design; user interface design; testing strategies and techniques; software systems' implementation; software systems' maintenance.
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 390 or equivalent.
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 390 or equivalent.
Additional Courses
CIS 530 - Information Technology Infrastructure (3 hours)
Enterprise information technology infrastructure including networking and telecommunications fundamentals, concepts, models, architectures, protocols, standards, communications, configuration, implementation, management, deployment software, firmware, hardware, distributed systems, file services, and software/hardware/network security issues. Cross listed with CIS 430. For cross-listed undergraduate/graduate courses, the graduate-level course will have additional academic requirements beyond those of the undergraduate course.
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 220 or equivalent, or consent of instructor. CIS 393 is strongly recommended.
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 220 or equivalent, or consent of instructor. CIS 393 is strongly recommended.
CS 560 - Fundamentals of Data Science (3 hours)
This course will combine two types of problem-solving: inferential thinking, and computational thinking applied to real-world problems. The course teaches critical concepts and skills in computer programming, at an accelerated pace, and an analysis of real-world datasets using statistical inference and a number of machine learning algorithms. The emphasis is on the use of tools and languages for data analysis and modeling.
Prerequisite: Graduate students in Computer Science or Computer Information Systems or Data Science and Analytics, who have taken: one semester of calculus-based statistics (IME 511 or equivalent); two semesters of computer programming or CS 541 or CS 502.
Prerequisite: Graduate students in Computer Science or Computer Information Systems or Data Science and Analytics, who have taken: one semester of calculus-based statistics (IME 511 or equivalent); two semesters of computer programming or CS 541 or CS 502.
CS 562 - Machine Learning (3 hours)
Machine learning and intelligent systems. Covers the major approaches to ML and IS building, including the logical (logic programming and fuzzy logic, covering ML algorithms), the biological (neural networks and deep learning, genetic algorithms), and the statistical (regression, Bayesian and belief networks, Markov models, decision trees and clustering) approaches. Students use ML to discover the knowledge base and then build complete, integrated, hybrid intelligent systems for solving problems in a variety of applications. Cross listed with CS 462. For cross-listed undergraduate/graduate courses, the graduate-level course will have additional academic requirements beyond those of the undergraduate course.
Prerequisite: Graduate students in Computer Science or Computer Information Systems or Data Science and Analytics who have taken: CS 560 and two semesters of calculus.
Prerequisite: Graduate students in Computer Science or Computer Information Systems or Data Science and Analytics who have taken: CS 560 and two semesters of calculus.
CS 563 - Knowledge Discovery and Data Mining (3 hours)
Brings together the latest research in statistics, databases, machine learning, and artificial intelligence that are part of knowledge discovery and data mining. Topics include algorithms for the data cleansing and preprocessing phase, selected supervised machine learning algorithms for modeling forecasting and classification, selected unsupervised machine learning algorithms, trend and deviation analysis, dependency modeling, integrated discovery and ensemble systems, meta-processing (boosting, stacking, etc.) and application case studies. Cross-listed with CS 463. For cross-listed undergraduate/graduate courses, the graduate-level course will have additional academic requirements beyond those of the undergraduate course.
Prerequisite: Graduate students in CS or CIS or Data Science and Analytics who have taken one semester of calculus-based statistics, for example: IME 511 or equivalent.
Prerequisite: Graduate students in CS or CIS or Data Science and Analytics who have taken one semester of calculus-based statistics, for example: IME 511 or equivalent.
CS 591 - Software Project Management (3 hours)
Methods of PMBOK-based management of software systems design and development projects, including systems view, main project management process groups and knowledge areas, management plans, project metrics and estimates, tools for project management, project reports and documentation. Cross listed with CIS 491 and CIS 591 courses. For cross-listed undergraduate/graduate courses, the graduate-level course will have additional academic requirements beyond those of the undergraduate course.
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 390 or equivalent, or consent of instructor.
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 390 or equivalent, or consent of instructor.
CS 592 - Requirements Development (3 hours)
Covers topics including basic concepts and principles of software requirements engineering, the requirements engineering process, requirements elicitation, requirements analysis, requirements specification, system modeling, requirements validation and requirements management, and techniques, methods, and tools for requirements engineering and software systems requirements modeling (including structured, object-oriented and formal approaches to requirements modeling and analysis).
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 210 or CIS 210 or equivalent, or consent of instructor.
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 210 or CIS 210 or equivalent, or consent of instructor.
CS 593 - Agile Software Development (3 hours)
Agile methodology, agile methods, and agile software engineering, including framework activities, SDLC models, requirements analysis, architectures, services, integrated development environments, testing, and quality issues. Cross listed with CS 493. For cross-listed undergraduate/graduate courses, the graduate-level course will have additional academic requirements beyond those of the undergraduate course.
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 390 or equivalent.
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 390 or equivalent.
In order to graduate from the online Master’s in Computer Science program, all candidates must satisfy the following departmental requirements:
- At least 33 hours of graduate-level coursework. The course CS 502 does not count as part of the total hours needed.
- To satisfy the core (breadth) requirement, four courses must be taken:
- CS 514
- CS 520
- CS 571
- CS 590
- To develop expertise in software engineering and data science, the following additional courses must be taken:
- CIS 530
- CS 560
- CS 562
- CS 563
- CS 591
- CS 592
- CS 593
- To satisfy the core (breadth) requirement, four courses must be taken:
- No “D” grades can be counted in the completion of requirements for the degree.
Every student must pass a written comprehensive examination that will be based on the core requirements for the program pursued.
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Considering an online Master of Science (M.S.) in Computer Science or a Computational Data Science Certificate to take your career to the next level? Your journey starts here. Complete the form to get more information about Bradley University’s Computer Science and Information Systems Department online programs.
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Bradley University is authorized to deliver online programs to US citizens and permanent residents residing in the United States. International students are encouraged to inquire about on-campus opportunities by visiting Bradley University International Admissions.
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