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Master ofComputer Science

Summary Courses Careers Costs and Aid

The Master of Computer Science (MCS) degree is a 30-credit online, interdisciplinary master’s program that aims to prepare students to drive the design, development, and deployment of software systems across a broad array of application domains to meet contemporary social and technical challenges.

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30 Credits$1,037 per credit

Gain Computer Science Skills to Excel in Engineering

  • Learn to solve complex business problems using algorithms and data structures, with a focus on designing and analyzing efficient algorithms and addressing computational problems.

  • Manage large-scale software projects, emphasizing software development life cycles, DevOps principles for project management, and operational aspects of software engineering.

  • Gain hands-on experience in developing big data solutions, designing applications for parallel computing, and understanding the architecture of data-intensive systems.

  • Complete training in machine learning, covering the entire life cycle from engineering data and building models to automating their deployment and monitoring their performance.

  • Acquire essential skills to effectively collaborate in data science teams, focusing on big data, machine learning, and data analytics projects.

  • Increase knowledge of distributed systems principles, including architecture analysis, implementation, and techniques for achieving reliability and fault tolerance.

Courses in the Master of Computer Science can provide you with the practical skills and knowledge required to succeed in roles where you collect, compile, and analyze data sets, develop software, design scientific and engineering applications, design and prototype AI systems, and solve complex computational problems. The highly interactive courses focus on in-demand areas such as full-stack development, data science, cloud computing, and AI, where students will not only be introduced to these topical areas but will also engage in hands-on system development by building fully functional systems.

You must successfully complete a total of 30 credits while maintaining a GPA of 3.0 or better in all course work, including:

  • 15 credits of core courses
  • 12 credits of electives
  • 3 credits of CSC 894: Computer Science Capstone, which includes building a fully functioning product

Core Courses

  • 3
    credits

    The Algorithms and Programming course is designed as the first course that students take in the online Master of Computer Science program. This course introduces the foundation of programming, data structures, and algorithms.

  • 3
    credits

    This course emphasizes the study of large-scale software systems through a software development project, serving as a central component.

  • 3
    credits

    This course provides a comprehensive exploration of distributed systems, focusing on the principles, design, and implementation of large-scale software systems across multiple computers.

  • 3
    credits

    This course provides an overview of the underlying building blocks of big data stack architecture and infrastructure.

  • 3
    credits

    This course equips students with the essential skills and knowledge required to actively participate as valuable team members in the field of data science, specifically focusing on big data, machine learning, and data analytics projects.

Elective Courses

  • 3
    credits

    This course facilitates students to learn and apply the concepts of distributed computing environments along with the distributed algorithms in varied real-world scenarios.

    • Prerequisite

      CSC 810

    • Concurrent

      CSC 830

  • 3
    credits

    This course explores the design, implementation, and management of distributed database systems. Students will gain a comprehensive understanding of the challenges and solutions associated with storing and managing large data sets across geographically dispersed locations.

    • Prerequisite

      CSC 830

  • 3
    credits

    This course emphasizes statistical ideas that inform the data life cycle, from generation of data through analysis and interpretation.

  • 3
    credits

    The data curation and cleaning course will explore the tools and techniques required for collecting, organizing, enriching, and maintaining data along with computational procedures to automatically identify and eliminate errors from large data sets.

  • 3
    credits

    This course provides an exploration of current and emerging big data solutions for handling large quantities of data in real time. In particular, this course investigates methods to design, develop, and implement several systems used for real-time data analysis and storage such as document databases, column-based databases, queueing systems, and real-time processing systems.

  • 3
    credits

    The data mining course is designed to provide students with a strong foundation and practical skills in data mining techniques. The course covers how to analyze large data sets, discover patterns, and effectively apply data mining algorithms.

    • Prerequisite

      CSC 841

  • 3
    credits

    Provides an intermediate-level treatment of statistical learning, the basis of artificial intelligence and machine learning methods.

    • Prerequisite

      CSC 841, CSC 850

  • 3
    credits

    This course provides a comprehensive introduction to Deep Learning, covering foundational concepts of neural networks, including multilayer perceptrons, convolutional neural networks, and recurrent neural networks.

    • Prerequisite

      CSC 850

    • Prerequisite

      CSC 851

  • 3
    credits

    This course is designed to provide students with a strong foundation and practical skills in deep learning–based NLP techniques and covers how to process and analyze text data, build and evaluate modern NLP models, and apply various algorithms and techniques to solve common NLP tasks.

    • Prerequisite

      CSC 852

Capstone Course

In this innovative course, students will have the opportunity to analyze, design, and develop cutting-edge distributed systems that are secure, high-performing, scalable, and reliable. By harnessing the power of machine learning and managing vast data volumes, students will solve real-world challenges, apply theoretical knowledge with practical tools, and push the boundaries of technological possibilities.

Through collaborative teamwork, thoughtful technology selection, and rigorous system analysis, learners will cultivate the skills and mindset necessary for continuous improvement and leadership in the evolving landscape of computer science.

  • 3
    credits

    In this course, students will have an opportunity to build a fully functioning product applying the principles and practices learned in their computer science courses to a real-world problem.

    • Prerequisite

      CSC 810, CSC 820, CSC 830, CSC 840, CSC 850

Course Availability

If you're ready to see when your courses will be offered, visit our public LionPATH course search (opens in new window) to start planning ahead.

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This degree program can empower you to become a sought-after expert capable of architecting and implementing large-scale, complex distributed and cloud-based solutions, big data applications, and artificial intelligence and machine learning systems. With this high-impact skill set, you’ll be well-positioned for rewarding careers and roles at the forefront of innovation in today’s fastest-growing industries.

Job Titles Related to This Degree

The following roles are often held by people with this type of degree:

  • Application Integration Engineer
  • Data Scientist
  • Software Development Engineer
  • Network and Security Engineer
  • DevOps Engineer
  • Cyber Security Engineer
  • Cloud Architect
  • Enterprise Systems Administrator

Employment Outlook for Occupational Fields Related to This Degree

Estimates of employment growth and total employment are provided by the U.S. Bureau of Labor Statistics and are subject to change. While these occupations are often pursued by graduates with this degree, individual outcomes may vary depending on a variety of factors. Penn State World Campus cannot guarantee employment in a given occupation.

Software Developers

17.9%
employment growth (10 years)
1,654,440
total employment

Computer and Information Systems Managers

17.4%
employment growth (10 years)
645,970
total employment

Data Scientists

36%
employment growth (10 years)
233,440
total employment

Information Security Analysts

32.7%
employment growth (10 years)
179,430
total employment

Computer Systems Analysts

10.7%
employment growth (10 years)
497,800
total employment

Computer Network Architects

13.4%
employment growth (10 years)
177,010
total employment

Database Architects

10.8%
employment growth (10 years)
64,770
total employment

Database Administrators

8.2%
employment growth (10 years)
73,180
total employment

Career Services to Set You Up for Success

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From the day you're accepted as a student, you can access resources and tools provided by Penn State World Campus Career Services to further your career. These resources are beneficial whether you're searching for a job or advancing in an established career.

  • Opportunities to connect with employers
  • Career counselor/coach support
  • Occupation and salary information
  • Internships
  • Graduate school resources 

Ready to Learn More?

Get the resources you need to make informed decisions about your education. Request information on this program and other programs of interest by completing this form.

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Ready to take the next step toward your Penn State master's degree?

Apply by May 1 to start May 18. How to Apply 

Learn about this program's tuition, fees, scholarship opportunities, grants, payment options, and military benefits.

Graduate Tuition

Graduate tuition is calculated based on the number of credits for which you register. Tuition is due shortly after each semester begins and rates are assessed every semester of enrollment.

2025–26 Academic Year Rates

Tuition Rates for the Fall 2025, Spring 2026, and Summer 2026 Semesters
How many credits do you plan to take per semester?Cost
11 or fewer$1,037 per credit
12 or more$12,448 per semester

2026–27 Academic Year Rates

Tuition Rates for the Fall 2026, Spring 2027, and Summer 2027 Semesters
How many credits do you plan to take per semester?Cost
11 or fewer$1,048 per credit
12 or more$12,572 per semester

Financial Aid and Military Benefits

Some students may qualify for financial aid. Take the time to research financial aid, scholarships, and payment options as you prepare to apply. Federal financial aid may only be used to pay for credits used to satisfy program requirements.

Military service members, veterans, and their spouses or dependents should explore these potential military education benefits and financial aid opportunities, as well.

Additional Cost of Attendance Details

To view the detailed list of cost of attendance elements:

Technical Requirements

Review the technical requirements for this program.

Note about additional hardware: It is a requirement for this online program that students have ready access to a document scanner that allows for the creation of PDF files, which will enable students to submit handwritten homework and exams in several of the mathematics-based courses.

Who Should Apply?

The Master of Computer Science program is designed for individuals with an undergraduate degree in computer science, engineering, information science, or related disciplines. It prepares students to excel in a wide range of careers across industries such as engineering, mathematics, natural sciences, social sciences, humanities, business, and health care. This program is ideal for individuals who are currently working or aspire to work in industry roles such as:

  • AI Product Engineer
  • Big Data Architect
  • Cloud Data Engineer
  • Cybersecurity Engineer
  • Distributed Systems Engineer
  • MLOps Engineer
  • Software Architect
  • Software Engineer
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Whether you are looking to finish your program as quickly as possible or balance your studies with your busy life, Penn State World Campus can help you achieve your education goals. Many students take one or two courses per semester.

Our online courses typically follow a 12- to 15-week semester cycle, and there are three semesters per year (spring, summer, and fall). If you plan to take a heavy course load, you should expect your course work to be your primary focus and discuss your schedule with your academic adviser.

To Finish Your Degree in One to Two Years

  • Take 2–3 courses each semester

To Finish Your Degree in Two to Three Years

  • Take 1–2 courses each semester

To Finish Your Degree in Three to Four Years

  • Take 1 course each semester

Timelines may vary based on course availability.

Convenient Online Format

This program's convenient online format gives you the flexibility you need to study around your busy schedule. You can skip the lengthy commute without sacrificing the quality of your education and prepare yourself for more rewarding career opportunities without leaving your home.

A Trusted Leader in Online Education

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Penn State has a history of more than 100 years of distance education, and World Campus has been a leader in online learning for more than two decades. Our online learning environment offers the same quality education that our students experience on campus.

Information for Military and Veterans

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Are you a member of the military, a veteran, or a military spouse? Please visit our military website for additional information regarding financial aid, transfer credits, and application instructions.

Note: This program is under review for GI Bill® eligibility, and you may experience delays attempting to use GI Bill benefits toward this program until it has been officially approved.

GI Bill® is a registered trademark of the U.S. Department of Veterans Affairs (VA). More information about education benefits offered by VA is available at the official U.S. government website at https://www.benefits.va.gov/gibill.

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Apply by May 1 to start May 18

Application Instructions

Deadlines and Important Dates

Complete your application and submit all required materials by the appropriate deadline. Your deadline will depend on the semester you plan to start your courses.

  • Summer Deadline

    Apply by May 1 to start May 18

  • Fall Deadline

    Apply by August 1 to start August 24

  • Spring Deadline

    Apply by December 1, 2026, to start January 11, 2027

Steps to Apply

  1. For admission to the J. Jeffrey and Ann Marie Fox Graduate School, an applicant must hold either (1) a baccalaureate degree from a regionally accredited U.S. institution or (2) a tertiary (postsecondary) degree that is deemed comparable to a four-year bachelor's degree from a regionally accredited U.S. institution. This degree must be from an officially recognized degree-granting institution in the country in which it operates.

    The program requires an undergraduate degree in computer science, engineering, or information science. Students from other disciplines will be considered based on prior course work, including the entrance requirements for mathematics and programming stated below. All applicants are expected to have earned a junior/senior grade-point average of 3.0 or higher.

    Mathematics Requirement

    Applicants must complete Calculus I (equivalent to Penn State's MATH 140).

    Programming Requirement

    Applicants must complete two introductory-level programming courses, where both courses used the same language. If you believe your work experience satisfies the background, you should include a recommendation letter from a technical colleague describing your coding contributions at work.

    Applicants not meeting these requirements may be asked to complete bridge course work before starting the program and must achieve a score of 80% or higher on assessments. These highly flexible, self-paced preparatory courses help build the foundational skills needed for success in graduate-level study and can serve as a pathway for individuals seeking to transition into the field of computer science. After completing, you will receive a badge that can be displayed digitally to recognize your accomplishment. Please reach out to [email protected] with any questions regarding these courses.

  2. You will need to upload the following items as part of your application:

    Official transcripts from each institution attended, regardless of the number of credits or semesters completed. Transcripts not in English must be accompanied by a certified translation. If you are a Penn State alum, you do not need to request transcripts for credits earned at Penn State but must list Penn State as part of your academic history.

    Test Scores — GRE/GMAT scores are NOT required and will not be reviewed.

    English Proficiency — The language of instruction at Penn State is English. With some exceptions, international applicants must take and submit scores for the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS). Minimum test scores and exceptions are found in the English Proficiency section on the Fox Graduate School's "Requirements for Graduate Admission" page. Visit the TOEFL website for testing information. Penn State's institutional code is 2660.

    References (2) — You will need to initiate the process through the online application by entering the names, email addresses, and mailing addresses of two (2) professional references. Upon submission of your application, an email will be sent to the recommenders requesting they complete a brief online recommendation regarding your commitment for success in an online program. Please inform the recommenders they must submit the form in order for your application to be complete.

    Program Specific Materials

    Résumé — Upload a one- to two-page résumé highlighting your full-time employment and/or military experience to the online application.

    Statement of Intent (one page) — Outline personal career goals and reasons for wanting to enroll in the program. This statement should be specific and include information about short- and long-term goals and how enrolling in the program may help achieve them. The statement of intent also offers applicants the opportunity to demonstrate writing and communication skills, specify examples of leadership, and provide pertinent information that will assist the committee in selecting candidates who can benefit from and contribute to the program.

  3. To begin the online application, you will need a Penn State account.

    Create a New Penn State Account

    If you have any problems during this process, contact an admissions counselor at [email protected].

    Please note: Former Penn State students may not need to complete the admissions application or create a new Penn State account. Please visit our Returning Students page for instructions.

  4. You can begin your online application at any time. Your progress within the online application system will be saved as you go, allowing you to return at any point as you gather additional information and required materials.

    • Choose Enrollment Type: "Degree Admission"
    • Choose "WORLD CAMPUS" as the campus

    Checking Your Status 
    You can check the status of your application by using the same login information established for the online application form. 

  5. 5. Complete the application.

    Penn State Fox Graduate School Application

Admissions Help

If you have questions about the admissions process, contact an admissions counselor at [email protected].

Customer service representative wearing a headset

Have questions or want more information? We're happy to talk.

For general questions about the program:
Dr. Amanda Neill
[email protected]

For general questions about Penn State World Campus:
World Campus Admissions Counselors
Phone: 814-863-5386
[email protected]

The Master of Computer Science graduate degree program is a collaborative effort between the School of Graduate Professional Studies at Penn State Great Valley and key partners, including Penn State Behrend, Penn State Eberly College of Science, Penn State Harrisburg, and Penn State College of Information Sciences and Technology.

Faculty

  • Youakim Badr

    • H.D.R., University of Lyon
    • Ph.D., Computer Science, National Institute of Applied Sciences (INSA-Lyon)
    • M.S., Mathematical Modeling and Scientific Software Engineering, Francophone University Agency
    • M.S., Computer Science, Lebanese University
    • B.S., Computer Science, Lebanese University

    Dr. Youakim Badr, professor of data analytics, teaches courses in analytics programming, analytics systems design, data mining and predictive analytics. His research interests include smart service computing, IoT, information security, big data, machine learning, and built-in analytics. Dr. Badr is a professional member of IEEE, a lifetime member of ACM, and associate member of the ACM special interest group on knowledge discovery and data mining (SIGKDD).

  • Adrian S. Barb

    • Ph.D., Computer Science, University of Missouri
    • MBA, Finance and Management Information Systems, University of Missouri
    • B.S., Industrial Engineering, University of Bucharest

    Dr. Adrian S. Barb, associate professor of information science, teaches databases, data mining, and big data courses. He has worked as a database programmer analyst as well as a web developer at University of Missouri. His research interests include data mining, knowledge discovery in databases, knowledge representation and exchange in content-based retrieval systems, semantic modeling and retrieval, conceptual change, ontology integration, and expert-in-the-loop knowledge generation and exchange.

  • Edward J. Glantz

    • Ph.D., Information Sciences and Technology, Penn State
    • MBA, Wharton School of Business, University of Pennsylvania
    • B.S., Mechanical Engineering, Penn State
    • B.A., General Arts and Science, Penn State

    Dr. Edward J. Glantz, P.E., has been with the College of IST faculty since 2009. Prior to joining IST, Dr. Glantz served 10 years as a faculty member of Penn State's Smeal College of Business. His career spans more than 20 years of managing technology, research, and marketing in the manufacturing and telecommunication industries, including startup work.

  • Everton Tavares Guimaraes

    • Ph.D., Software Engineering, Pontifical Catholic University of Rio de Janeiro
    • M. S., Computing and Systems, Federal University of Rio Grande do Norte
    • B.S., Information Technology, Federal Institute of Education, Science, and Technology

    Everton Tavares Guimaraes is an assistant professor specializing in software engineering. He teaches algorithms, programming, software development, architecture, and mobile computing. For a decade, he has partnered with companies domestically and internationally. His research focuses on empirical software engineering, software quality (e.g., maintenance and evolution), technical debt, AI techniques, and mobile software engineering.

  • Russell Martin

    • M.S., Business Administration
    • B.S., Management Information Systems

    After spending 20 years in corporate America and working with/for several Fortune 500 companies as a software engineer and solutions architect, Russell Martin joined the University as a professor in computer science and software engineering. He has taught courses on programming language concepts, database design, mobile application development, web services, and distributed systems. In all of his courses, he pushes his students to understand the relevant technologies in the industry and how to properly navigate the world of technology in a project-style environment, where possible.

  • Scott Roths

    • Ph.D., Statistics,  Penn State
    • B.S., Mathematics,  Kansas State

    Dr. Scott Roths' primary interest is in teaching statistics, including probability and multivariate methods. He teaches both online and at the University Park campus.

  • Raghvinder S. Sangwan

    • Ph.D., Computer and Information Sciences, Temple University
    • M.S., Computer Science, West Chester University
    • B.S., Genetics and Plant Breeding, Haryana Agricultural University

    Dr. Raghvinder S. Sangwan is a professor of software engineering with expertise in the analysis, design, and development of large-scale, software-intensive systems and the use of AI engineering to design and develop intelligent systems that are safe, secure, and trustworthy. His research focuses on the improvement of these practices, and he has taught related courses to engineers and project managers at many prestigious academic, government, and industry organizations worldwide. Dr. Sangwan actively consults for Siemens Corporate Technology in Princeton, New Jersey, and holds a visiting scientist appointment at the Software Engineering Institute at Carnegie Mellon University in Pittsburgh, Pennsylvania. He is a distinguished contributor and senior member of IEEE and a senior member of ACM.

  • Satish Srinivasan

    • Ph.D., Information Technology, University of Nebraska at Omaha
    • M.S., Industrial Engineering and Management, Indian Institute of Technology, Kharagpur
    • B.S., Information Technology, Bharathidasan University

    Dr. Satish Srinivasan is an associate professor of information science in the engineering division at Penn State Great Valley. He teaches courses related to database design, data mining, data collection and cleaning, design and implementation of predictive analytics system, network and web securities, and business process management. His research interests include social network analysis, data mining, machine learning, big data and predictive analytics, and bioinformatics.

Ready to take the next step toward your Penn State master's degree?

Apply by May 1 to start May 18. How to Apply 

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