Master of Science (M.S.) Major in Computer Science Online

Prepare for career growth by mastering advanced computer science concepts in areas like artificial intelligence, software engineering, and system design.

Apply by: 8/5/26
Start class: 8/19/26
Apply Now

Program Overview

Meet the future head-on with an online M.S. in Computer Science

Build advanced computer science expertise you can apply immediately in the workplace. Texas State University’s online Master of Science in Computer Science is designed for working professionals who want to deepen their technical capabilities and bridge the gap between foundational knowledge and real-world application.

Through flexible online course work and faculty-guided projects, you’ll develop hands-on experience designing, implementing, and deploying scalable software, artificial intelligence, and computing systems. Course work emphasizes practical application, allowing you to build skills you can use on the job and apply toward a professional portfolio.

Graduates are prepared to solve complex technical problems, lead high-impact initiatives, and pursue advanced roles across industry—or continue on to doctoral study.

Tools and technologies you’ll use:

  • Programming Languages: Python, C++, Java
  • AI/ML Frameworks: PyTorch, TensorFlow, and modern deep learning libraries
  • Cloud Computing Platforms: AWS, Microsoft Azure
  • Databases: Relational, NoSQL, and vector databases (e.g., PostgreSQL, MongoDB, FAISS)
  • Software Engineering Tools: Version control and collaboration tools (e.g., Git, GitHub)
  • Distributed & Scalable Systems: Tools and frameworks for building high-performance and distributed applications
Tools and technologies you’ll use:
  • Programming Languages: Python, C++, Java
  • AI/ML Frameworks: PyTorch, TensorFlow, and modern deep learning libraries
  • Cloud Computing Platforms: AWS, Microsoft Azure
  • Databases: Relational, NoSQL, and vector databases (e.g., PostgreSQL, MongoDB, FAISS)
  • Software Engineering Tools: Version control and collaboration tools (e.g., Git, GitHub)
  • Distributed & Scalable Systems: Tools and frameworks for building high-performance and distributed applications

As a student in this online master’s in computer science program, you will learn how to:

  • Design and analyze efficient algorithms for complex problems
  • Apply advanced artificial intelligence concepts and techniques
  • Develop and manage complex computing and operating systems
  • Design secure, scalable, and high-performance software systems
  • Communicate technical concepts clearly to technical and nontechnical audiences
As a student in this online master’s in computer science program, you will learn how to:
  • Design and analyze efficient algorithms for complex problems
  • Apply advanced artificial intelligence concepts and techniques
  • Develop and manage complex computing and operating systems
  • Design secure, scalable, and high-performance software systems
  • Communicate technical concepts clearly to technical and nontechnical audiences

Career opportunities:

  • Software Engineer
  • Systems Engineer
  • Machine Learning Engineer
  • Data Engineer
  • Information Security Analyst
  • Computer Systems Analyst
  • AI Systems Engineer / Applied AI Engineer
Career opportunities:
  • Software Engineer
  • Systems Engineer
  • Machine Learning Engineer
  • Data Engineer
  • Information Security Analyst
  • Computer Systems Analyst
  • AI Systems Engineer / Applied AI Engineer

Also available:

We offer a variety of student-centered online degrees that can help you advance. Explore other graduate programs.

Total Tuition $15,014*
Duration As few as 18 months
Credit Hours 30
Apply Now

Need More Information?

Call 833.690.1245 today!

Call 833.690.1245 today!

Tuition

Pay as you go, one course at a time

Tuition for the online master’s degree program in computer science is affordable and paid by the course, so you can achieve your academic goals while remaining within your budget.

View full tuition

Program Per Credit Hour Per Course Per Program
M.S. Computer Science $500 $1,501 $15,014*

Tuition breakdown

Total Tuition $15,014*
Per Credit Hour $500

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toward earning your degree?

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Calendar

Here are some key dates to plan around

The Texas State M.S. in Computer Science program is delivered in a convenient online learning format that offers maximum flexibility for working adults like you. Choose the start date that fits your goals.

View Full Calendar +

TermStart DateApp DeadlineDocument DeadlineRegistration DeadlineTuition DeadlineClass End DateTerm Length
Fall 1 20268/19/268/5/268/12/268/19/268/13/2610/7/268 weeks
Fall 2 202610/8/269/24/2610/1/2610/8/2610/1/2612/10/268 weeks

Now Enrolling

Apply by 8/5/26
Start Class 8/19/26

Admissions

See what you need to start an accredited online computer science degree program

Apply to the M.S. in Computer Science online program quickly and easily with our streamlined admission process. Review the admission requirements below and take the next step toward your professional goals.

View all admission requirements

To be eligible to earn your M.S. in Computer Science degree online from Texas State University, you must have the following:

  • Completed online application
  • Nonrefundable application fee of $55 ($90 for international*)
  • Baccalaureate degree from an accredited college or university in a computer science-related area. Graduates of programs outside this area may be required to satisfy program prerequisites before full admission into the program
  • Copy of official transcripts from each institution where course credit was granted
  • Minimum 2.75 GPA overall or 2.75 GPA in your last 60 hours of undergraduate course work (plus any completed graduate courses)
  • Resume/CV detailing work experience, extracurricular and community activities, and honors and achievements
  • Three letters of recommendation from persons best able to assess your ability to succeed in graduate school

For applicants without a U.S. bachelor’s degree (or equivalent)**:
You must submit an approved English proficiency exam score that meets the minimum program requirements.

  • Official TOEFL iBT scores required with a 78 overall and minimum individual module scores of
    • 19 listening
    • 19 reading
    • 19 speaking
    • 18 writing
  • Official PTE scores required with a 52 overall
  • Official IELTS (academic) scores required with a 6.5 overall and minimum individual module scores of 6.0
  • Official Duolingo scores required with a 110 overall
  • Official TOEFL Essentials scores required with an 8.5 overall

**Exemption: Applicants who have earned a bachelor’s degree or higher from a regionally accredited U.S. institution or an equivalent degree from a country on our exempt countries list are not required to submit an English proficiency exam score.

Transcripts may be sent electronically to [email protected] or mailed to:

TXST One Stop
Texas State University – Graduate Admissions
601 University Dr.
San Marcos, TX 78666

*Texas State defines an on-campus international student as anyone with a nonimmigrant visa status, including H-1B visa holders, or those seeking a visa to enroll. If you are not a U.S. citizen, permanent resident, refugee, or asylee, you will be classified as an international applicant.

An online international student is someone who holds citizenship in another country, is not a U.S. permanent resident, and resides outside the U.S. while enrolling in an online program.

Students who are not on a visa but are graduating from a Texas high school after three years in residence are considered domestic applicants.

If you are a U.S. citizen, permanent resident, refugee, or asylee, you are considered a domestic applicant.

Admission Requirements

  • Minimum 2.75 GPA
  • No GMAT/GRE required
  • All official transcripts

Courses

Preview courses in this online master’s degree in computer science program

To graduate from the Master of Science in Computer Science online degree program, you must complete a total of 30 credit hours, including 12 credit hours of core courses and 18 credit hours of electives.

Expand All

Students will select one course from this group. 

Duration: 8 Weeks weeks
Credit Hours: 3
This course provides a study of modern operating systems, including network, distributed, and real-time systems.
Duration: 8 Weeks weeks
Credit Hours: 3
This course provides a study of network and communication systems. Students will be required to perform verification and implementation of protocols.
Duration: 8 Weeks weeks
Credit Hours: 3
This course covers computer system organization for the management of data. Topics include data models, data model theory, optimization and normalization, integrity constraints, query languages, and intelligent database systems.

Students will select one course from this group. 

Duration: 8 Weeks weeks
Credit Hours: 3
This course focuses on the principles of programming languages. Topics covered include programming paradigms, concepts of programming languages, formal syntax and semantics, and language implementation issues.
Duration: 8 Weeks weeks
Credit Hours: 3
This course covers advanced topics in automata theory, grammars, Turing machines, decidability, and algorithmic complexity. A strong background in both data structures and discrete mathematics is required.
Duration: 8 Weeks weeks
Credit Hours: 3
This course provides an introduction to the design and analysis of parallel algorithms, parallel architectures, and computers.
Duration: 8 Weeks weeks
Credit Hours: 3
The course covers the software life cycle, emphasizing system analysis and design, including a survey of methodologies based on data flows and objects. The course includes a professional ethics component.

Students will take the following core courses:

Duration: 8 Weeks weeks
Credit Hours: 3
This course provides an introduction to algorithm design and analysis, computational complexity, and NP-completeness theory.
Duration: 8 Weeks weeks
Credit Hours: 3
This course covers knowledge representation, knowledge engineering, parallel and distributed artificial intelligence (AI), heuristic searches, machine learning and intelligent databases, and implementation of systems in high-level AI languages.

18 hours of electives for 30 total hours

Duration: 8 Weeks weeks
Credit Hours: 3
This course covers fundamental concepts and techniques, plus recent developments in data mining and information retrieval. It provides relevant research training and practice opportunities. May not be taken for credit if the student has received credit for CS 4315.
Duration: 8 Weeks weeks
Credit Hours: 3
Duration: 8 Weeks weeks
Credit Hours: 3
Provides broad introduction to machine learning, including learning theory, and recent topics like support vector machines and feature selection. Covers basic ideas, intuition, and understanding behind modern machine learning methods. Discusses applications like face recognition, text recognition, biometrics, bioinformatics, and multimedia retrieval.
Duration: 8 Weeks weeks
Credit Hours: 3
This course covers various aspects of producing secure computer information systems that provide guaranteed controlled sharing. Emphasis is on software models and design, including discovery and prevention of computing systems security vulnerabilities. Current systems and methods are examined and critiqued.
Duration: 8 Weeks weeks
Credit Hours: 3
Duration: 8 Weeks weeks
Credit Hours: 3
The course covers the software life cycle, emphasizing system analysis and design, including a survey of methodologies based on data flows and objects. The course includes a professional ethics component.

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