A flexible and affordable Data Science 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 Illinois Computer Science, 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, Illinois Computer Science 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.
Read our blog posts:
- The Master of Computer Science in Data Science: A Top-Ranked Degree That Fits Your Life
- Why a Quality CS Degree Matters to Employers
Sit in on an Illinois course:
Take one of these courses or Specializations to learn from Illinois MCS degree instructors and complete assignments that give you a head start on degree courses.
$19,200 ($600 per credit hour) plus additional fees:
Coursera fees: $79 per each open Coursera course that is applied toward the MCS-DS. (Each credit-bearing course of enrollment at the University of Illinois requires concurrent enrollment in two associated Coursera courses for lecture content and some assessments.)
Note: If the required Coursera course has already been completed before the credit-bearing MCS-DS course started, students do not need to pay again.
ProctorU fees: Exams proctored through ProctorU will be billed when an exam is scheduled, at $8.75 (30-min. exam), $14.75 (1-hr. exam), $21.50 (90-min. and 2-hour exam), or $30.25 (3-hour exam).
Amazon Web Services fees: Vary, depending on the course.
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.
AT A GLANCE
- 12 - 36 months
- 32 credit hours (8 courses)
- ~$21,000Total Cost
- Completely online
Start your application
The next cohort starts on August 26th, 2019.
May 30th, 2019
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.
- 32 credit hours (8 courses)
- 12 - 36 months
What Every MCS-DS Student Learns...
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.
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 core Data Mining coursework can be focused on discovering patterns in structured data or retrieving information from unstructured data in the form of natural language text, and the program is flexible enough to allow students interested in data mining to study both.
Cloud computing is essential for learning, visualizing, and mining big data. The cloud computing coursework can be focused on the cloud programming for infrastructure or for applications, but students interested in cloud computing can study both.
The degree experience is...
The same kind of courses you’ll find on campus, with the flexibility to learn when and where you want.
Collaborate with a global network of classmates, instructors, and alumni.
Innovative courses with lectures from some of the world’s best instructors and hands-on projects.
Practical courses designed to help you master skills that you can start applying to your career right away.
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. Transcripts will only indicate “Master of Computer Science,” and will not mention data science or the mode of delivery. You are free to refer to the degree as Master of Computer Science in Data Science on your resume, LinkedIn, or anywhere else that would be helpful.
MCS-DS topics include data visualization, machine learning, data mining, cloud computing, statistics, and information science.
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. For more information visit Illinois application information page.
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 and are admitted to the degree program, 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.
Additional details about applying to the Master of Computer Science in Data Science are available on the application page.
Coursera financial aid is available for the Specializations component of the program only.
Yes, each course or Specialization is available separately, but you will not earn graduate credit at the University of Illinois.
To earn credit from the University of Illinois, you must be admitted as a degree-seeking student and registered for credit-bearing course(s).
No. You need to pay tuition when you enroll in each individual course. That means you’ll only pay for your courses as you take them.
Yes, you can get started with these Specializations and courses on Coursera to try out the degree program works before you apply. If you apply and are accepted to the program, your work counts towards your degree learning.
Coursera does not grant credit, and does not represent that any institution other than the degree granting institution will recognize the credit or credential awarded by the institution; the decision to grant, accept, or transfer credit is subject to the sole and absolute discretion of an educational institution.