Ball State University's Master of Science in Computer Science program offers a unique opportunity for learners from all backgrounds to enter the computer science field. This 36-credit program combines foundational knowledge with advanced topics in machine learning, data analytics, cybersecurity, and software engineering. With performance-based admission and flexible learning options, students can complete their degree while maintaining their careers.
Instructors:
English

Course Start Date:
January 06, 2025
Applications Deadline:
Spring 2025
Duration:
24 Months
₹ 40,587
Overview
Ball State University's MS in Computer Science program is designed to make advanced computer science education accessible to learners from all backgrounds. This 36-credit program combines fundamental computer science principles with cutting-edge applications in machine learning, cybersecurity, and software engineering.
Why MSc (Master of Science)?
The program stands out for its innovative performance-based admission process, eliminating traditional barriers like entrance exams and prior CS experience. Students benefit from Ball State's recognized excellence in online education, dedicated success specialists, and comprehensive career support.
What does this course have to offer?
Key Highlights
36-credit curriculum structure
No CS background required
Performance-based admission
Hands-on practical learning
Dedicated success specialist
Career coaching and support
Flexible online format
Who is this programme for?
Career switchers seeking CS expertise
Working professionals pursuing advancement
Graduates from non-CS backgrounds
Technology enthusiasts
Professionals seeking formal CS education
Minimum Eligibility
Bachelor's degree (any field)
Complete three pathway courses with 3.0 GPA
Access to computer and internet
Who is the programme for?
The program follows a performance-based admission model requiring completion of three pathway courses with a 3.0 GPA. The curriculum consists of 36 credits: 18 core credits, 6 research credits, and 12 elective credits. Students can complete coursework across fall, spring, and summer semesters.
Important Dates
Selection process
How to apply?
Curriculum
The curriculum combines foundational computer science courses with advanced specialized topics. Core courses cover programming, data structures, and algorithms, while electives explore machine learning, data analytics, cybersecurity, and software engineering. The program emphasizes practical application through hands-on learning experiences.
There are 3 semesters in this course
The MS in Computer Science curriculum is structured to provide both fundamental knowledge and specialized expertise. Students begin with essential programming and computer science concepts before advancing to specialized areas. The program includes hands-on projects and modern technology exposure, ensuring practical skill development alongside theoretical understanding.
Core Courses (12-18 credits)
This series of courses offers a comprehensive curriculum in computer science, covering foundational programming, data structures, algorithms, data analytics, cybersecurity, and software engineering. CS 617, Introduction to Programming, serves as a foundational course where students learn the basics of programming, including syntax, logic, and problem-solving techniques, providing a solid base for further studies. CS 601, Computer Programming and Data Structures, expands on this by introducing more advanced programming concepts and data structures, emphasizing how to efficiently store and manipulate data in software applications. CS 602, Discrete Structures and Algorithms, focuses on the mathematical foundations of computer science, teaching students about discrete structures such as sets, graphs, and trees, as well as algorithms for solving computational problems. CS 621, Data Analytics, introduces students to the tools and techniques used in extracting insights from data, providing a solid foundation in data manipulation, statistical analysis, and visualization techniques relevant to modern data-driven applications. CS 647, Cybersecurity and Secure Software, equips students with the knowledge and skills needed to develop secure software systems, focusing on principles of cybersecurity, encryption, and strategies to protect applications from various types of cyber threats. Finally, CS 690, Software Engineering, covers the software development lifecycle, teaching students about design, testing, and maintenance of large-scale software systems, and providing practical skills for working in team-based environments on real-world software projects. Together, these courses prepare students for careers in software development, cybersecurity, and data analytics, equipping them with a well-rounded, industry-relevant skill set.
CS 617 Introduction to Programming (3 credits)
CS 601 Computer Programming and Data Structures (3 credits)
CS 602 Discrete Structures and Algorithms (3 credits)
CS 621 Data Analytics (3 credits)
CS 647 Cybersecurity and Secure Software (3 credits)
CS 690 Software Engineering (3 credits)
Research Courses (choose 6 credits)
This advanced set of courses in computer science offers students the opportunity to explore specialized topics, conduct independent research, and deepen their understanding of complex computational theories and applications. CS 639, Seminar in Computer Science, allows students to engage in in-depth discussions and presentations on current trends and challenges in the field, offering up to 6 credits based on participation and research outcomes. CS 668, Graphs, Algorithms and Applications, focuses on the theoretical and practical aspects of graph theory and its application to real-world problems, such as network design, routing, and optimization, providing students with a strong foundation in algorithmic thinking. CS 681, Applications of Computability, introduces the theory of computability and its real-world applications, covering topics such as Turing machines, computational complexity, and the limitations of computation in various domains. CS 699, Independent Study in Computer Science, offers students the flexibility to explore a topic of their choice in greater depth, guided by a faculty advisor, with the possibility of earning up to 6 credits for research or project work in a specific area of interest. Finally, CS 679, Research Topics in Computer Science, encourages students to explore cutting-edge research in computer science, focusing on emerging technologies, novel algorithms, or interdisciplinary areas, and offers up to 6 credits depending on the scope and depth of the research undertaken. These courses provide students with a comprehensive understanding of advanced topics in computer science, fostering critical thinking, problem-solving, and independent research skills essential for pursuing careers in academia, industry, or research.
CS 639 Seminar in Computer Science (up to 6 credits)
CS 668 Graphs
Algorithms and Applications (3 credits)
CS 681 Applications of Computability (3 credits)
CS 699 Independent Study in Computer Science (up to 6 credits)
CS 679 Research Topics in Computer Science (up to 6 credits)
Elective Courses (12 credits)
This set of courses offers a diverse range of advanced topics in computer science and data science, preparing students for the evolving demands of the tech industry with a focus on web development, operating systems, artificial intelligence, machine learning, data storage, and cloud computing. CS 618, Full Stack Web Development, covers the complete development of web applications, teaching students both front-end and back-end technologies, as well as frameworks and best practices for creating dynamic and scalable websites. CS 619, Advanced Operating Systems and Networking, dives into the complex interactions between operating systems and networking protocols, giving students a deep understanding of how to design and manage systems that interact efficiently with networked devices. CS 626, Topics in Artificial Intelligence, explores current advancements in AI, with a focus on innovative techniques, theories, and real-world applications of machine learning, natural language processing, and robotics. CS 654, Machine Learning and Data Mining, provides an in-depth exploration of machine learning algorithms, data mining techniques, and how to apply these methods to analyze large datasets and extract valuable insights. DSCI 604, Data Storage and Management, introduces students to various storage technologies and data management systems, focusing on how to design and optimize databases for large-scale data environments. DSCI 605, Data Visualization, teaches students how to create compelling visual representations of complex data, helping them to communicate insights effectively through graphs, charts, and dashboards. Finally, DSCI 606, Introduction to Cloud Computing, offers an overview of cloud technologies and services, teaching students how to leverage cloud infrastructure for scalable storage, computing, and application development. Together, these courses provide a comprehensive skill set for students pursuing careers in software development, data science, AI, and cloud computing, combining theoretical knowledge with practical, hands-on experience.
CS 618 Full Stack Web Development (3 credits)
CS 619 Advanced Operating Systems and Networking (3 credits)
CS 626 Topics in Artificial Intelligence (3 credits)
CS 654 Machine Learning and Data Mining (3 credits)
DSCI 604 Data Storage and Management (3 credits)
DSCI 605 Data Visualization (3 credits)
DSCI 606 Introduction to Cloud Computing (3 credits)
Programme Length
The program is designed to be completed in 24 months, with courses offered in fall, spring, and summer semesters. Students typically take 1-2 courses per term to balance work and study commitments.
Tuition Fee
Tuition is $489 per credit for the 36-credit program. Students can utilize flexible payment options, paying per credit as they progress. Financial aid opportunities are available to help make the program more affordable.
Fee Structure
Payment options
Financial Aid
Learning Experience
Students experience a comprehensive online learning environment with access to modern educational technology and resources. The program combines self-paced study with interactive elements, supported by dedicated success specialists and faculty engagement.
University Experience
Ball State provides extensive online resources including library access, tutoring services, and career support. Students receive personalized guidance from Student Success Specialists and can participate in virtual networking opportunities. Optional campus visits are available for events like graduation.

About the University
Established in 1918, Ball State University is a public research university located in Muncie, Indiana. The university offers a diverse range of undergraduate and graduate programs across various fields, including education, business, communication, and the arts. With a commitment to student success and community engagement, Ball State serves over 20,000 students and is known for its innovative teaching methods and vibrant campus life.
20440
Total Enrollment
14874
Undergraduate Students
5566
Graduate Students
Affiliation & Recognition
Higher Learning Commission
National Council for Accreditation of Teacher Education
Association of American Colleges and Universities
Career services
The Career Center at Ball State University provides extensive support for students' career development. Services include resume workshops, interview preparation, job fairs, and networking events. The center also offers personalized career counseling to help students identify their career goals and develop strategies to achieve them.
85%
Job Placement Rate
2000+
Career Counseling Sessions
50+
Workshops Offered

Course Start Date:
January 06, 2025
Applications Deadline:
Spring 2025
Duration:
24 Months
₹ 40,587
Whom you will learn from?
Learn from top industry experts who bring real-world experience and deep knowledge to every lesson. The instructors are dedicated to help you achieve your goals with practical insights and hands-on guidance.
Instructors
Department Chair of the Department of Computer Science and Director of Computer Science Graduate Program and Associate Professor of Computer Science
Dr. Jennifer Coy serves as the chair of the Department of Computer Science at Ball State University. With nearly 20 years of experience, she has taught a broad array of courses, mentored students, and fostered industry-academia partnerships. Dr. Coy holds both a B.S. in Computer Science and Engineering and a B.S. in Engineering Physics from the University of Toledo. She completed her M.S. and Ph.D. in Physics at Purdue University, focusing her dissertation on computational astrophysics. After earning her graduate degrees, Dr. Coy taught computer science at two other universities before joining Ball State. Her research interests center on applying computing to various scientific fields, aiming to drive new discoveries through interdisciplinary collaboration. Currently, she is developing computational models to enhance our understanding of Radon’s radioactive decay and its potential implications for dark matter within the solar system. Beyond her professional life, Dr. Coy enjoys camping with her family, running half marathons, and reading.
Professor of Mathematical Sciences
Dr. Begum Munni is an Assistant Professor of Mathematics at Ball State University. She holds a Ph.D. in Mathematics and specializes in areas such as algebra and combinatorics. Dr. Munni is actively involved in teaching undergraduate and graduate courses, mentoring students, and conducting research in her field. Her contributions to mathematics education and research are reflected in her published works and participation in academic conferences. Additionally, she is committed to fostering a supportive learning environment for her students and enhancing their understanding of mathematical concepts.
Testimonials
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they’re here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
Instructors
Department Chair of the Department of Computer Science and Director of Computer Science Graduate Program and Associate Professor of Computer Science
Dr. Jennifer Coy serves as the chair of the Department of Computer Science at Ball State University. With nearly 20 years of experience, she has taught a broad array of courses, mentored students, and fostered industry-academia partnerships. Dr. Coy holds both a B.S. in Computer Science and Engineering and a B.S. in Engineering Physics from the University of Toledo. She completed her M.S. and Ph.D. in Physics at Purdue University, focusing her dissertation on computational astrophysics. After earning her graduate degrees, Dr. Coy taught computer science at two other universities before joining Ball State. Her research interests center on applying computing to various scientific fields, aiming to drive new discoveries through interdisciplinary collaboration. Currently, she is developing computational models to enhance our understanding of Radon’s radioactive decay and its potential implications for dark matter within the solar system. Beyond her professional life, Dr. Coy enjoys camping with her family, running half marathons, and reading.
Assistant Teaching Professor of Geography
Aihua Li is a teaching assistant professor in the Department of Geography and Meteorology and the Data Science program at Ball State University. Dr. Li’s research focuses on interdisciplinary geospatial sciences within environmental and ecological contexts. Her work involves the analysis, modeling, and visualization of extensive geospatial data across various scales.
Instructors
Department Chair of the Department of Computer Science and Director of Computer Science Graduate Program and Associate Professor of Computer Science
Dr. Jennifer Coy serves as the chair of the Department of Computer Science at Ball State University. With nearly 20 years of experience, she has taught a broad array of courses, mentored students, and fostered industry-academia partnerships. Dr. Coy holds both a B.S. in Computer Science and Engineering and a B.S. in Engineering Physics from the University of Toledo. She completed her M.S. and Ph.D. in Physics at Purdue University, focusing her dissertation on computational astrophysics. After earning her graduate degrees, Dr. Coy taught computer science at two other universities before joining Ball State. Her research interests center on applying computing to various scientific fields, aiming to drive new discoveries through interdisciplinary collaboration. Currently, she is developing computational models to enhance our understanding of Radon’s radioactive decay and its potential implications for dark matter within the solar system. Beyond her professional life, Dr. Coy enjoys camping with her family, running half marathons, and reading.
Professor of Mathematical Sciences
Dr. Begum Munni is an Assistant Professor of Mathematics at Ball State University. She holds a Ph.D. in Mathematics and specializes in areas such as algebra and combinatorics. Dr. Munni is actively involved in teaching undergraduate and graduate courses, mentoring students, and conducting research in her field. Her contributions to mathematics education and research are reflected in her published works and participation in academic conferences. Additionally, she is committed to fostering a supportive learning environment for her students and enhancing their understanding of mathematical concepts.
Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.
Complete three pathway courses with 3.0 GPA, no prior CS background needed
The program can be completed in 24 months
$489 per credit for 36 credits total