Master of Computer Science

Deepen your computer science knowledge and accelerate your career with a top ranked degree program for computing professionals.

Who is this degree for:

Designed for computing professionals, the Master of Computer Science is a graduate degree credential that builds skill and knowledge in advanced topics of computer science. The degree is suitable for students with a baccalaureate degree in a computing-related field as well as students who want to demonstrate computer science expertise in addition to a degree in another field.

AT A GLANCE
  • 12-36 months
    Each course will require 10-12 hours per week, depending on the student’s background
  • 8 courses
  • $19,200 plus fees
  • Completely online

Start your application

The next cohort starts on January 14th, 2019.


Final Deadline:

October 15th, 2018

Applications are open three times per year, for cohorts starting in the fall, spring, and summer.

Want to learn more before applying?

After answering a few short questions, we’ll be able to help you find out if you’re qualified to apply and give you more information about the degree program.

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Academics

The Master of Computer Science is a non-thesis degree that requires 32 credit hours of coursework. Students can complete the eight courses required for the Master of Computer Science at their own pace, in as little as one year or as many as five years. Students receive lectures through the Coursera platform, but are advised and assessed by Illinois faculty and teaching assistants on a rigorous set of assignments, projects, and exams required for university degree credit.

  • 8 courses
  • 7 projects
  • 12-36 months
    Each course will require 10-12 hours per week, depending on the student’s background

Some of your courses and projects may include:

Architecture, Compilers and Parallel Computing

Learn parallel programming to achieve peak performance from multi-core CPU and many-core GPU computer architectures, as well as the languages, compilers and libraries best suited for different parallel applications and platforms.

Artificial Intelligence

Build your knowledge of the statistical models and numerical optimizations of machine learning with application in computer vision, natural language processing and intelligent user interaction.

Database and Information Systems

Learn the basics of database systems and different data mining methods for extracting knowledge and insight both 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 both function-based and object-oriented methods for analysis and design. Learn how to see a large software project from its original specification through its implementation, testing and maintenance. Additionally, you will learn how to manage large enterprise-level codebases.

Graphics and Human-Computer Interaction

Learn the fundamentals of interactive computing to promote an effective synergy between the computer and its human 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 ultimately build a cloud computing platform. Master ways to create applications that utilize cloud resources effectively.

Scientific Computing

Discover the fundamentals of numerical analysis and how it applies to accurate solutions to the large linear systems used for everything from simulation in scientific applications to optimization in machine learning to the physics of your favorite video game.

The degree experience is...

100% ONLINE
100% ONLINE

The same courses you’ll find on campus, with the flexibility to learn when and where you want.

INTERACTIVE
INTERACTIVE

Collaborate with a global network of industry leading classmates, instructors, and alumni.

ENGAGING
ENGAGING

Innovative courses with lectures from some of the world’s best instructors and hands-on projects.

CAREER-FOCUSED
CAREER-FOCUSED

Practical courses designed to help you master skills that you can start applying to your career right away.

When you graduate, you’ll be able to:

  • Success

    Apply mathematical foundations, algorithmic principles, and computer science theory in the modeling and design of computer-based systems in a way that demonstrates comprehension of the tradeoffs involved in design choices

  • Success

    Analyze a problem and identify and define the computing requirements appropriate to its solution

  • Success

    Design, implement, and evaluate a computer-based system, process, component, or program

  • Success

    Apply design and development principles in the construction of software systems of varying complexity

Admissions

Requirements

Applicants for the degree program must have:

  • A bachelor’s degree
  • 3.0/4.0 undergraduate GPA or higher (from the last two years of bachelor’s degree coursework)
  • Sufficient background in object-oriented computer programming, data structures & algorithms (e.g. a “data structures” course or comparable knowledge)
  • Not already completed a graduate degree in computer science. (Those who already hold a graduate degree in computer science can complete the program to earn a Master’s Certificate that they can list alongside their existing graduate degree in CS.)

Recommendations

Applicants for the degree program are recommended to have:

  • A bachelor’s degree in a computing field
  • 3.2/4.0 undergraduate GPA or higher
  • Programming experience demonstrated by employment or a list of programming projects
  • Programming experience with C++ and/or Java

Start your application

The next cohort starts on January 14th, 2019.


Final Deadline:

October 15th, 2018

Applications are open three times per year, for cohorts starting in the fall, spring, and summer.

About University of Illinois

24

Nobel Laureates

450,000

Global Alumni Network

#5

Computer Science program in the U.S.

Faculty

ChengXiang Zhai

ChengXiang Zhai

Indranil Gupta

Indranil Gupta

Jiawei Han

Jiawei Han

John C. Hart

John C. Hart

Reza Farivar

Reza Farivar

Roy H. Campbell

Roy H. Campbell

Ready to start your application?

The next cohort starts on August 16, 2018

Final Deadline:

May 30, 2018

Want to learn more before applying?

Frequently Asked Questions

  • Yes. Students admitted to the degree program, who complete all degree requirements, will earn a Master of Computer Science degree and diploma from the University of Illinois.

  • To earn the accredited degree, you must be admitted as a degree-seeking student through the Graduate College at the University of Illinois. However, you may begin taking courses and Specializations on Coursera at any time, including prior to admission into the program.

  • You may either apply and commit to the full Master of Computer Science program immediately, or start with a Data Mining or Cloud Computing Specialization on Coursera and build toward the full degree. If you’re sure you want to earn an accredited Master of Computer Science, apply for admission to the degree program. However, if you’re not certain that the full program is right for you, you can complete one or more Specializations prior to applying. If you decide to apply later, you’ll still need to complete the for-credit courses to earn your degree, but you won’t need to take the Specializations again.

    If you’re even a little bit interested in the full degree program, we suggest requesting more information by completing the form above. This option allows you to learn more about the application process and program requirements with no immediate commitment.

  • Yes, each course or Specialization is available separately.

  • Enroll at the University of Illinois to earn official university credit through relevant enhanced courses while completing Specializations on Coursera.

  • We expect Masters-level CS students to be able to learn new languages in order to use the best tool to solve a problem, but we try to be flexible with languages when possible to allow students to program in the language in which they are most comfortable. Students should already be proficient in at least one compiled object-oriented programming language.