Master of
Computer Science

Fall 2020 Application Opens February 1

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$333 per
credit hour

10 Courses

1.5 - 3 years

Top 10

On Your


It's no secret that the demand for highly skilled technical workers is at an all-time high. At present, there are more than 500,000 openings for computing jobs and fewer than 50,000 computer science graduates entering the market each year. To enable students to capitalize on these opportunities, the University of Texas at Austin is proud to announce that beginning in fall 2019, it will be partnering with the edX learning platform to take its master’s in computer science program online.

Built to provide maximum flexibility, whether you’re a full-time student or a working professional, UT’s new online master’s in computer science was designed to enable students to further their education on their own terms. The program will provide students with the same world-class education enjoyed by our on-campus students by utilizing the same curriculum and the same renowned faculty. The master of computer science online program will provide the same rigorous training and the same credential as our existing top-ten-ranked graduate program.  The resulting degrees will be indistinguishable (will not say on-campus or online).  By combining instruction from the elite faculty of UT Austin with the flexibility of online delivery, students now have the opportunity to become subject matter experts in a way that is both more affordable and consistent with their existing lifestyles.

The Department of Computer Science is known for its broad strength across all facets of computer science, including artificial intelligence and robotics, networks, security, data mining and visualization, systems, bioinformatics, theory and formal methods and verification. Regardless of where your career path leads, the master of computer science online degree can help you acquire the skills to get there.

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Program Overview Video

Watch to learn more about:

  • Curriculum
  • Program information
  • Eligibility
  • Application process and deadlines


Strong candidates will be expected to submit the following materials:

1. A bachelor’s degree in computer science from a regionally accredited institution with a cumulative GPA of 3.0 or higher.  Other degrees may be considered (particularly in related fields such as electrical engineering, computer engineering or mathematics), however, applicants who do not hold a degree in computer science should have prior coursework or experience equivalent to the following UT Computer Science undergraduate courses:

Exceptions will be made on a case-by-case basis.  If you have evidence of gaining content knowledge on these subjects through a course or through work experience, please detail that in your CV and personal statement.

2. Official Transcript. Within 48 hours of the submission of your application, you will receive an email from the Graduate and International Admissions Center directing you to the MyStatus page where you will be asked to upload your transcripts.  Please do not mail these credentials.  For additional information regarding the submission of transcripts to UT-Austin, please see

3. Official Test Scores (GRE, TOEFL/IELTS)

  • GRE General Test scores
    • There is no minimum GRE test score, however applicants admitted to the UT Computer Science graduate program usually have high quantitative GRE scores and a math background that includes study through some discrete math.
    • The GRE cannot be waived.
  • TOEFL or IELTS score for international applicants*
    • The minimum scores considered acceptable for admission by the Graduate School are:
      • TOEFL: 79 on the Internet-based test (iBT)
      • IELTS: An overall band of 6.5 on the Academic Examination

*International applicants who are from a country where English is the only official language are exempt from this requirement. Additionally, applicants are exempt from the requirement if they possess a bachelor's degree from a U.S. institution or an institution in a country where English is the only official language. The requirement is not waived for applicants who have earned a master's - but not a bachelor's degree from a similar institution.

4.  Optional: CV, Personal Statement and up to three letters of recommendation.

Fall 2020 Enrollment

  • Application Opens: February 2, 2020
  • Priority Deadline: March 15, 2020 (11:59 p.m. CST)
    • Students will be notified of their admissions decision in April.
  • Regular Deadline: April 15, 2020 (11:59 p.m. CST)
    • Students will be notified of their admissions decision in May.

If you are applying by the priority deadline, the application, transcripts, test scores, CV*, personal statement* and recommendation letters* should be received by the priority deadline.  Otherwise, everything should be submitted by the regular deadline. (*optional)

Tuition          $10,000 (full program)
                        $333 per credit hour

Fees              Some additional institutional fees may apply.

Tuition and fees are the same for U.S. and international students.



The curriculum will be comprised of 30 credits hours of total study, including 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. Machine Learning, Data Centers, Security) that will allow students to tailor their studies to their own interests.

Course Availability

FALL 2019

CS 391L Machine Learning
Adam Klivans & Qiang Liu
Computing systems that automatically improve their performance with experience, including various approaches to inductive classification such as version space, decision tree, rule-based, neural network, Bayesian, and instance-based methods; as well as computational learning theory, explanation-based learning, and knowledge refinement.
CS 380L Advanced Operating Systems
Vijay Chidambaram
Study of the formal structure, design principles, organization, implementation, and performance analysis of multiprogramming and/or multiprocessor computer systems.
CS 380P Parallel Systems
Calvin Lin & Chris Rossbach
The objective of this course is to provide students with strong background on concurrency fundamentals along with experience with a diversity of both classical and modern approaches to managing and exploiting concurrency, including shared memory synchronization, parallel architectures such as GPUs, as well as distributed parallel frameworks such as MPI and map-reduce. Material will be presented through readings and discussion of background material as well as occasional recent research papers when appropriate. The course requires a number of programming and project assignments to provide direct experience with design, programming, and measurement methodologies for concurrent systems.
CS 395T Optimization
Sujay Sanghavi & Constantine Caramanis
This class covers Linear Programming and Convex Optimization. These are fundamental conceptual and algorithmic building blocks for applications across science and engineering. Indeed any time a problem can be cast as one of maximizing / minimizing and objective subject to constraints, the next step is to use a method from linear or convex optimization. Covered topics include formulation and geometry of LPs, duality and min-max, primal and dual algorithms for solving LPs, Second-order cone programming (SOCP) and semidefinite programming (SDP), unconstrained convex optimization and its algorithms: gradient descent and the newton method, constrained convex optimization, duality, variants of gradient descent (stochastic, subgradient etc.) and their rates of convergence, momentum methods. 
CS 395T Deep Learning
Philipp Krähenbühl
This class covers advanced topics in deep learning, ranging from optimization to computer vision, computer graphics and unsupervised feature learning, and touches on deep language models, as well as deep learning for games.
CS 395T Advanced Linear Algebra for Computation
Maggie Myers & Robert van de Geijn
Linear algebra invariably lies at the core of techniques that are of critical importance to computational and data scientists.  In this course, you learn advanced concepts in linear algebra, practical algorithms for matrix computations, and how floating point arithmetic as performed by computers affects correctness.
CS 388G Algorithms: Techniques and Theory 
Vijaya Ramachandran & Greg Plaxton
Advanced topics in algorithm design and analysis including algorithmic paradigms, maximum flow, randomized algorithms, data structures, NP-completeness and approximation algorithms. No programming is involved in this course.
CS 395T Online Learning and Optimization
Constantine Caramanis & Sanjay Shakkottai
This class has two major themes: algorithms for convex optimization and algorithms for online learning. The first part of the course will focus on algorithms for large scale convex optimization. A particular focus of this development will be for problems in Machine Learning, and this will be emphasized in the lectures, as well as in the problem sets. The second half of the course will then turn to applications of these ideas to online learning.
CS 394R Reinforcement Learning: Theory and Practice
Peter Stone & Scott Niekum
Introduces the theory and practice of modern reinforcement learning.  Reinforcement learning problems involve learning what to do—how to map situations to actions—so as to maximize a numerical reward signal.  The course will cover model-free and model-based reinforcement learning methods, especially those based on temporal difference learning and policy gradient algorithms.
Sampling of courses under consideration for launch in subsequent semesters:
CS 380S Theory and Practice of Secure Systems
A survey of modern security, designed to introduce the basic techniques used in the design and analysis of secure systems.

Frequently Asked Questions

What degree is earned at the end of the program?
Master of Science in Computer Science (MSCS)

Is this degree equivalent to the UT Master of Science in Computer Science degree offered to on-campus students?
Yes, your diploma will read exactly as those of an on-campus graduate.

What is the curriculum?
The curriculum will consist of ten courses total or 30 hours. Students will take a combination of foundational coursework and elective options. Through completion of the foundational coursework, students will gain a broad understanding of the field. Students will also have significant elective flexibility to pursue a course of study best tailored to their professional aspirations.

How will courses be determined?
Courses will provide the requisite skillsets one would expect from a master’s level of study (e.g. algorithms, programming languages) while also focusing on subject matter that is in high demand within industry (e.g. deep learning, data centers, secure systems).

Where is a list of courses?
A complete list of initial courses will be announced at a later date. Some courses under consideration include machine learning, reinforcement learning, deep learning/neural networks, programming languages, algorithms, software engineering, data centers, secure systems, virtualization, scientific computing, parallel computing and programming for performance.

Will I have any instructor or TA interaction?
Interaction between instructors and/or TA’s will be available through email or an online discussion board.

Do I have to maintain a certain GPA in order to stay in the program?
Students must maintain a 3.0 GPA throughout the course of the program. If a student drops below 3.0, he or she will have one semester to bring up the GPA. If the student fails to do this, they will be dismissed from the program.

How many credit hours will I need in order to graduate?
30 credit hours, which equals 10 courses.

How long will the program take me to complete?
The program can be completed in 1.5-3 years and the curriculum is highly flexible.

How many courses will I take to complete my degree?
10 courses

How many courses will I be allowed to take at a time?
The university has not defined a limit on the number of online courses a student can take simultaneously. However, online master’s courses are of comparable rigor to the traditional courses. We strongly recommend no more than nine hours of course work during the long semester and two courses during the summer.

Can you start taking classes in the fall or the spring?
Yes, you can start taking classes in either semester.

Will I have access to career services?
Students will have access to the university's online job board as well as fall and spring career fairs.

When will the semester start and end?
The program will follow the timeline of the traditional semester. The university calendar can be found here.

Can students apply for financial aid?
Graduate students pursuing a master’s online may apply for federal, state and institutional financial aid programs administered by the Office of Financial Aid by completing a Free Application for Federal Student Aid (FAFSA).

Does the University offer scholarships for this program?
The University does not offer scholarships for this program.

Will I be expected to pay the entire cost up front?
You will pay tuition for each course separately. Additionally, students may be required to pay an institutional fee during each semester of enrollment.

How do I apply?
The application is currently available on our site, here is a checklist to guide you through the application process.

When can I apply?
We will begin accepting applications Spring 2019.

If I meet the admissions criteria, will I be automatically admitted to the program?
No applicant will be automatically admitted to the program. All applications will be reviewed by a faculty committee to make certain those admitted have the ability to succeed in the program.

Is there a certain score needed on the GRE to be admitted?
There is no minimum GRE test score, however applicants admitted to the CS graduate program usually have high quantitative GRE scores and a math background that includes study through some discrete math. If you feel that your test scores are not valid indicators of your ability, you should explain your concerns in your statement of purpose.

How do I check the status of my application?
GIAC MyStatus: This is the status check site for the Graduate International Admissions Center (GIAC). GIAC verifies application information, test scores, residency and admissions GPA calculations/equivalencies. If you have questions about the information your MyStatus page, please contact GIAC.

Can I submit my GRE/TOEFL scores and transcripts after the application deadline?
All GRE/TOEFL scores, transcripts, CV’s, personal statement and recommendation letters (if submitting), must be submitted by the application deadline.

Can I apply for both the traditional master’s program and the master’s online program?
You can apply for both programs but you must fill out two separate applications and upload documents to both systems. You can find information about applying to the traditional master’s program here.

Where should ETS send my test scores?
For GRE and TOEFL scores, the Educational Testing Service (ETS) institution code for UT-Austin is 6882. It is not necessary to use a department code. There is no institutional code for the IELTS examination. For IELTS scores, have an official paper score report sent to the Graduate and International Admissions Center.

Is the TOEFL required for International Students?
Yes, the TOEFL or the IELTS is required for international applicants. The minimum TOEFL score considered acceptable for admission by the graduate school is a 79 on the Internet-based test (iBT). For the IELTS, a student must have an overall band of 6.5 on the Academic Examination. International applicants who are from a country where English is the only official language are exempt from this requirement. Additionally, applicants are exempt from the requirement if they possess a bachelor’s degree from a U.S. institution or an institution in a country where English is the only official language. The requirement is not waived for applicants who have earned a master’s – but not a bachelor’s – degree from a similar institution.

With regards to transcript submittal from a foreign university, do I need to submit a foreign credential evaluation from WES or another organization?
A foreign credential evaluation is not required. If a transcript is written in a language other than English, a complete and official English translation must be uploaded together with the original transcript.

Will the university ask my recommender for a letter of recommendation?
Through the ApplyTexas system, you will be given the opportunity to submit three recommenders and provide contact information. The system will send an email to your recommenders directing them to a website where they may upload their letters. In addition, the MyStatus page of ApplyTexas offers a self-service feature you can use to resend the request email to your recommenders, if necessary. Use it to supply an alternate email address if your recommender’s spam filter blocks the original request or has removed the link. You can also add a new recommender or revise your right-to-view status from “retained” to “waived.”