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[University of Illinois] Master of Computer Science

Master Of Computer Science

This programme requires 32 credit hours of graduate coursework, completed through eight graduate-level courses. You are required to choose four of these eight courses from core areas of computer science, and three of these eight courses are at the advanced graduate level (500-level). The online Master of Computer Science (MCS) currently offers coursework in the core areas of artificial intelligence, databases, human-computer interaction, software engineering, scientific computing, and high-performance computing.

If you are interested in data science, you can select the Master of Computer Science in Data Science (MCS-DS) track. This track is for those who want to prepare for data science careers by learning how to mine useful insights from massive datasets. The Master of Computer Science in Data Science (MCS-DS) confers the same MCS degree, but focuses on core competencies in machine learning, data mining, data visualization, and cloud computing, as well as interdisciplinary data science courses offered in cooperation with the Department of Statistics and the School of Information Science.

Course Duration

12 to 36 months
Each course requires 10 to 12 hours per week, depending on your background

Course Content

Build expertise and career skills in the most important computer science topics. Courses and projects cover subjects like:

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 Human-Computer Interaction
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.

Scientific Computing
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.

Who is this degree for?

This degree is for computing professionals who want to build skills in advanced topics in computer science, such as artificial intelligence, database & information systems, parallel computing, graphics, systems & networking, scientific computing, and more. This degree will accelerate your career and help you move into leading a team of engineers.

Admission Requirements

Applicants for the degree programme must have:

  • An eligible bachelor's degree
  • 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)
  • Not already completed a graduate degree in computer science, computer engineering or a closely related field.

Application Deadline

Applications are open three times per year. Click the button below to find out more.

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