A flexible and affordable degree from one of the top Computer Science programs in the world focused on one of the hottest fields of the new millennium.

Enroll in the Master of Computer Science in Data Science (MCS-DS) and gain access to the computational and statistical knowledge needed to turn big data into meaningful insights. Build expertise in four core areas of computer science—data visualization, machine learning, data mining, and cloud computing—while learning key skills in statistics and information science. This completely online degree is an affordable gateway to one of the most lucrative and fastest growing careers of the new millennium.

The MCS-DS is offered by CS @ ILLINOIS, a U.S. News & World Report top five CS graduate program, in collaboration with the University’s Statistics Department and top-ranked iSchool. Join our alumni network of entrepreneurs, educators, and technical visionaries, who have revolutionized the way people communicate, shop, conduct business, and are entertained. From the ILLIAC to Blue Waters, OpenMP to MPI, Mosaic to YouTube, and the first vectorizing compilers to LLVM, CS @ ILLINOIS has long been at the forefront of excellence in computing and education.

Who is this degree for:

Professionals who want to use big data to understand the world, discover new insights, and optimize their decision-making will find value in the MCS-DS program. Analyzing the rising tide of data has become important to a wide range of fields, including the humanities, medicine, and business, as well as engineering and the sciences. Students will gain a strong foundation that will enable them to bring data science to bear on these areas. The program is designed so that students can complete it at their own pace as they balance their personal and professional commitments. Most students complete the degree in less than three years, though it can be completed in as little as one year or, if needed, as many as five years.


Tuition for the MCS-DS is $600 per credit hour, for a total of $19,200 for the complete 32 credit hour degree. There are additional fees from Coursera, ProctorU, and, depending on the course, Amazon Web Services. Though the department does not have any assistantships or scholarships available for this program, domestic students may qualify for Federal Student Aid, since the MCS-DS is accredited by the Higher Learning Commission.


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

What Every MCS-DS Student Learns

  • Machine Learning: The core Applied Machine Learning course focuses on tool-oriented and problem-directed lessons in machine learning. Application areas include computer vision, natural language processing, interpreting accelerometer data, and understanding audio data.
  • Data Visualization: The core Data Visualization course shows how to present data effectively for human understanding, starting with database visualization tools like Tableau and concluding with programming with D3.js to create reactive web pages for narrative data storytelling.

The degree experience is...

  • 100% ONLINE: The same courses you’ll find on campus, with the flexibility to learn when and where you want.
  • INTERACTIVE: Collaborate with a global network of industry-leading classmates, instructors, and alumni.
  • ENGAGING: Innovative courses with lectures from some of the world’s best instructors and hands-on projects.
  • CAREER-FOCUSED: Practical courses designed to help you master skills that you can start

When you graduate, you’ll be able to:

  • Utilize cloud computing to learn, visualize, and minr new insights from big data.
  • Analyze available data to inform critical decisions.
  • Study data scientifically, and use it to prove hypotheses.
  • The program effectively, using the right tools for the job.



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. including 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 in Data Science that they can list alongside their existing graduate degree in CS.)


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, and
  • programming experience with C++ and/or Java.

Application Process

All applicants must submit an application form, supplemental form, three letters of reference, a statement of purpose, resume, and official transcripts from all completed university coursework. TOEFL / IELTS scores may be required for international applicants.

About University of Illinois

Since its founding in 1867, the University of Illinois at Urbana-Champaign has earned a reputation as a global leader in research, teaching, and public engagement. With our land-grant heritage as a foundation, we pioneer innovative research that tackles global problems and expands the human experience. Our transformative learning experiences are designed to produce alumni who desire to make a significant, societal impact. Illinois is a pioneer in the innovative distance and online education, led by the Center for Innovation in Teaching and Learning. CS @ ILLINOIS has partnered with the School of Information Sciences and the Department of Statistics to offer the Master of Computer Science in Data Science.

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Last updated November 16, 2018
This course is Online
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Sep 2019
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