Master of Computer
Science Online

Curriculum & Courses


The curriculum incorporates foundational coursework that provides a broad understanding of the field and elective coursework on subject matter that is in high demand within industry (e.g. advanced systems design, machine learning and artificial intelligence ) that will allow students to tailor their studies to their own interests. Students receive weekly courses through the edX platform, and are advised and assessed by UT Austin faculty and staff on rigorous assignments, programming projects, and comprehensive exams that blend computer science theory and applied, project-based learning using real-world tools and environments. Students also participate in peer grading of assignments to ensure a firm grasp on the material.

At Your Own Pace

Built to provide maximum flexibility, whether you’re a full-time student or a working professional, the online master’s in computer science was designed to enable students to further their education on their own terms. Many people will complete the degree within two to three years, but you can take longer if needed.

Rigorous Courses

Online program students will enjoy the same rigorous training and the same credential as our existing top-ten-ranked graduate program. The resulting degrees will be indistinguishable.

Foundational Knowledge

Our courses will teach you not only the methods and techniques you will use in computer science, but also the mathematical foundations of why those methods and techniques are appropriate. Our faculty want you to leave not only knowing how to do something, but also why it works, and why that method is better than others.



Coursework Overview

three required courses


seven elective courses


10 Courses

This is a 30-hour program with 9 hours of required courses and 21 hours of electives. One class from each course category—Theory, Systems and Applications—are required. Elective courses are opportunities to specialize in areas such as advanced systems design, machine learning and artificial intelligence.

Required Courses

One class from each of the following:

  • Applications: Deep Learning, Machine Learning, Reinforcement Learning: Theory and Practice, Linear Algebra
  • Systems: Advanced Operating Systems, Parallel Systems
  • Theory: Algorithms: Techniques and Theory, Online Learning and Optimization, Optimization

Elective Courses

  • Course Selections: Android Programming (coming Fall 2020), Quantum Computing (coming Spring 2021)
  • Note: Any course can be counted towards Elective hours once the required course requirements are met.


  • Optimization

    Sujay Sanghavi & Constantine Caramanis

    Theory Course

    See Course Details

  • Deep Learning

    Philipp Krähenbühl

    Applications Course

    See Course Details

  • Advanced Linear Algebra for Computing

    Maggie Myers
    & Robert van de Geijn

    Applications Course

    See Course Details

  • Algorithms: Techniques and Theory

    Vijaya Ramachandran
    & Greg Plaxton

    Theory Course

    See Course Details

  • Online Learning and Optimization

    Constantine Caramanis
    & Sanjay Shakkottai

    Theory Course

    See Course Details

  • Reinforcement Learning: Theory and Practice

    Peter Stone
    & Scott Niekum

    Applications Course

    See Course Details


Enrollment Options

Courses are offered by semester and follow The University of Texas at Austin academic calendar. Students may begin courses in either the fall or spring semester. Once enrolled, fall and spring semesters are required, whereas the summer semester is optional.

Students may enroll in the MCSO program on a part-time or full-time basis. For working professionals, we recommend taking one to two courses per semester.

Students are allowed a maximum of six years to complete the MCSO degree.

Take the Next Step

Advance your computer science career with UT Austin's Master of Computer Science Online.