Learn more about computer science
This program does not have specific admission requirements and only admission to Kennesaw State University is required.
General Education Core Curriculum Requirements Specific to This Major
Area A2: Students must take MATH 1113 or higher.
Area D1: Students must take MATH 1179 or higher.
Area D2: Students must take two four-hour laboratory sciences in Area D2. Students must choose from CHEM 1211/L, CHEM 1212/L, PHYS 1111/L*, PHYS 1112/L, PHYS 2211/L*, PHYS 2212/L, BIOL 1107/L, or BIOL 1108/L. *Students cannot take both PHYS 1111/L and PHYS 2211/L nor PHYS 1112/L and PHYS 2212/L.
Degree Progression Requirements
Progression through the program requires students to successfully complete or transfer the equivalent of CSE 1321, CSE 1321L, CSE 1322, and CSE 1322L with a grade of ‘B’ or better in all four courses.
- Artificial Intelligence
- Data Science
- Cyber and Network Security
Double Owl Pathways
Related Minors or Certificates Available
- Computer Science Minor
- High Performance Computing Certificate
- Robotics Programming Certificate
CS 3502: Operating Systems
The course covers the basic concepts, design and implementation of operating systems. Topics include an overview of basic computing hardware components, operating system structures, process management, memory management, file systems, input/output systems, protection and security. The Windows and/or UNIX/Linux operating systems will be reviewed as example systems.
CS 3626: Cryptography
The course covers both mathematical and practical foundations of cryptography. Topics include basic number theory for cryptography, conversion of text, and implementation using a programming language. The course includes historical cryptography, symmetric cryptography, asymmetric cryptography, hash functions, and well-known attack strategies with countermeasures. Exercises cover programming of simple cryptography in a programming language.
CS 3642: Artificial Intelligence
The primary objective of this course is to provide a introduction to the basic principles and applications of Artificial Intelligence. It covers the basic areas of artificial intelligence including problem solving, knowledge representation, reasoning, decision making, planning, perception and action, and learning – and their applications. Students will design and implement key components of intelligent agents of modern complexity and evaluate their performance. Students are expected to develop familiarity with current research problems, research methods, and the research literature in AI.
CS 4265: Big Data Analytics
This course covers algorithms and tools that are needed to build MapReduce applications with Hadoop or Spark for processing gigabyte, terabyte, or petabyte-sized datasets on clusters of commodity hardware. A wide range of data algorithms will be discussed in this course.