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Master of Computer Science

University of Illinois

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.

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.

Students interested in data science can select the Master of Computer Science in Data Science (MCS-DS) track. This track is for students 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.

When you graduate, you’ll be able to:

– Apply mathematical foundations, algorithmic principles, and computer science theory to real-word 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

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  • Provider: University of Illinois
  • Cost: $21,440 USD
  • Effort: 10 - 12 hours per week
  • Duration: 1 - 3 years
  • Language: English


  • Architecture, Compilers, and Parallel Computing
  • Artificial Intelligence and Machine Learning
  • Database and Information Systems
  • Formal Methods, Programming Languages, and Software Engineering
  • Graphics, Visualization, and Interactive Computing
  • Systems and Networking
  • Scientific Computing