The degree program is designed to be flexible and fast — you can earn your Master’s with 100% online courses in as little as 12 months, while applying your learning immediately to your job.
- 12 – 36 Months (Each course requires 10 – 12 hours per week, depending on the student’s background)
- 8 courses
- 32 credit hours
- Completely Online
- View Course Syllabus
Online Course Details:
The Online MCS program requires 32 credit hours of graduate coursework, completed through eight graduate-level courses. The MCS requires that four of these eight courses are chosen from four different core areas of computer science, and that three of these eight courses are at the advanced graduate level (500-level). The Online MCS currently offers coursework in the core areas of artificial intelligence, databases, interactive computing, software engineering, scientific computing, and high-performance computing. For those interested in enhancing their tech skills, our Reviews of Fundamentals of Computing Specialization offer an in-depth analysis of this essential course series.
Applicants for the degree program must have:
- An eligible bachelor’s degree (check to see if your degree is eligible)
- 3.0 or higher undergraduate GPA (from the last two years of bachelor’s degree coursework)
- A strong background in object-oriented computer programming, data structures, and algorithms (this should include a “data structures” course or comparable experience). If you do not have graded and transcripted prerequisite CS coursework in these areas, consider enrolling in our Accelerated Computer Science Fundamentals Specialization that is designed to help you prepare for the Online MCS Entrance Exam which can strengthen your application for admission.
- Not already completed a graduate degree in computer science, computer engineering or a closely related field
Additional Admissions Recommendations:
Applicants for the degree program are recommended to have:
- A bachelor’s degree in a computing field (or transcripted coursework in fundamental CS coursework, e.g. data structures)
- 3.2/4.0 undergraduate GPA or higher
- Programming experience with C++ or Java
All applicants must submit an application form, the supplemental form, three letters of reference (not required, but highly recommended), a statement of purpose, resume, and official transcripts from all completed university coursework. TOEFL/IELTS scores may be required for international applicants. Additional details about applying to the Master of Computer Science can be found here. All applicants must pay the application fee before their application can be reviewed. There are no exceptions.
Master of Computer Science:
Build expertise and career skills in the most important computer science topics. Courses and projects cover subjects like:
Gain insights into Computer Science programming course through our detailed review, which explores the curriculum’s focus on practical coding skills.
Architecture, Compilers, and Parallel Computing
Learn parallel programming and how to achieve peak performance from multi-core CPU and many-core GPU architectures. Master languages, compilers, and libraries that are suited for various parallel applications and platforms.
Artificial Intelligence and Machine Learning
Build your knowledge of the fundamental statistical models and numerical optimizations of machine learning, including deep learning, with applications in computer vision, natural language processing and intelligent user interaction.
Database and Information Systems
Learn the basics of database systems as well as data mining methods for extracting insight from structured datasets (e.g. for a sales recommendation system) as well as unstructured data (e.g. from natural language text).
Formal Methods, Programming Languages, and Software Engineering:
Discover the fundamentals of software engineering, including function-based and object-oriented methods for analysis and design. Learn to manage a large software project from specification through implementation, testing, and maintenance. You‘ll also learn to manage large enterprise-level codebases.
Graphics, Visualization, and Interactive Computing
Learn the fundamentals of interactive computing that promote synergy between the computer and its user. The Data Visualization course, for example, shows how to present and manipulate data to communicate understanding and insight to the public.
Systems and Networking
Learn how to network computers into distributed systems and build a cloud computing platform or an Internet of Things. Understand how to create applications that utilize cloud resources with programming projects that utilize Amazon Web Services and Microsoft Azure.
Discover the fundamentals of numerical analysis, and how it’s applied to scientific and engineering simulations, with applications ranging from creating video game worlds to virtual medicine.
When you graduate, you’ll be able to:
- Apply mathematical foundations, algorithmic principles, and computer science theory to real-world problems
- Analyze a problem and identify the computing requirements appropriate to its solution
- Design, implement and evaluate a computer-based system, process, component, or program
- Apply design and development principles to construct software systems of varying complexity.