Students may select a concentration from one of several areas. Each concentration is designed to offer a structured set of elective courses around an organized theme without increasing time to degree completion. Concentrations are only available to computer science majors.

Computer Science Concentrations

Big Data

The era of Big Data has ushered in a host of exciting opportunities for computer scientists. Students in our data concentration will study both advanced computational and analytic tools such as data mining, large-scale optimization, data analytics, data storage, and data-intensive computing, as well as modern interdisciplinary applications of big data in industries as diverse as healthcare, transportation, energy, and finance.

Computer Systems

Computer systems is a broad field of study that offers students the opportunity to develop expertise in operating systems, distributed systems, networks, and security. These skillsets support a wide array of applications and technologies such as cloud computing, virtual machine technology, network and systems reliability, and the Internet of Things.


​The Cybersecurity concentration (formerly known as INFOSEC) is available to students who want to intensively study cybersecurity and privacy. Students will receive instruction on a wide range of cybersecurity related topics like network security and cryptography.

Game Development

Texas has the second largest concentration of game studios in the U.S., and as mobile, online, and social platforms improve, more and more opportunities will arise. Game development is an inherently interdisciplinary field, which is why Computer Science, Fine Arts, and Radio-Television-Film have jointly developed the world-class Game and Mobile Media Applications program. GAMMA students will take classes like Computer graphics, Game Technology, and a project-based capstone course.

Machine Learning & Artificial Intelligence

The concentration for Machine Learning and Artificial Intelligence is ideal for students who desire to learn how to program computer systems to 'learn' from data and perform complex tasks normally associated with human-level intelligence. ML/AI includes the opportunity to study topics such as computer vision, natural language processing, robotics, machine learning, deep learning, and knowledge acquisition and representation.

Mobile Computing

Mobile computing has revolutionized the way we interact with the world. This concentration explores important topics in mobile computing, including Internet and wireless networks, mobile app development, cloud computing, network security, and Internet of Things. These topics are applicable to a virtually endless array of industries.

Social Impact Stamp

Complement your mastery of technical skills with a broad awareness of how the technologies created by them and by the computer science industry impact larger society by earning a Social Impact Stamp. The stamp, separate from technical concentrations, can be earned alongside a concentration or independently.

The Stamp curriculum is designed to raise a student's critical consciousness—their understanding of how computer science intersects with the social forces that shape the world, their ability to identify potential for misuse of computer science to perpetuate social injustices, and their awareness of their agency to change those injustices. Students pursuing a Social Impact Stamp have the opportunity to put this understanding to practice via a Social Impact Capstone project. The knowledge gained from the Social Impact Stamp empowers graduates to guide development of future technology towards social good.

  • Students must complete the following:

    • CS103F: Ethical Foundations of Computer Science
    • Either CS378: Behavioral Ethics or CS349: Contemporary Issues in Computer Science
    • CS173G: Social Impact Capstone will be first offered in Spring 2024
      • Restricted to students who have completed or are concurrently enrolled in all other requirements
  • Choose four courses from the following list:

    • C S 371N/378: Natural Language Processing with Greg Durrett or Eunsol Choi (Fall 21 and later)
    • C S 363M: Principles of Machine Learning I with Angela Beasley (Fall 22 and later)
    • C S 370s that combine technical and social impact concepts will be considered on a case-by-case basis. If you want your 370 considered for this stamp, please indicate that on the form (by writing “For Social Impact Stamp” in big letters). It will then be considered as part of the approval process.
    • More courses coming soon!