Require knowledge of data science

Earn your Master’s, learn from pioneering Illinois faculty, and gain the data science skills that are transforming business and society. Illinois Computer Science offers a specialized track that includes both MCS degree requirements and data science-focused coursework. This degree is right for anyone who not only wants to learn to extract knowledge and insights from massive data sets, but also wants full command of the computational infrastructure to do so.
The Master of Computer Science in Data Science (MCS-DS) leads the MCS degree through a focus on core competencies in machine learning, data mining, data visualization, and cloud computing, It also includes interdisciplinary data science courses, offered in cooperation with the Department of Statistics and the School of Information Science.
If you select the Data Science track, your courses and projects will focus on:
Machine Learning: Coursework focusing on tool-oriented and problem-directed approaches to machine learning with applications in computer vision, natural language processing, geopositioning, and voice & music.
Data Visualization: Coursework designed to show you how to create effective and understandable data presentations. Learn database visualization tools like Tableau. Use D3.js to develop reactive web pages for narrative data storytelling.
Data Mining: This course shows you how to discover patterns in structured data. You’ll also learn to retrieve information from unstructured data sources, such as natural language text.
Cloud Computing: Coursework on the cloud computing technology, infrastructure and application development that is essential for supporting the discovery and extraction of knowledge from big data.

When you graduate, you’ll be able to:

  • Utilize cloud computing to scale up analysis and processing of big data
  • Visually and computationally analyze available data to inform critical decisions
  • Study data scientifically, and use it to form, prove, and defend hypotheses
  • Program effectively, using the right tools for the job

Sit in on an Illinois course:


    Take one of these courses or Specializations to learn from Illinois MCS-DS degree instructors and complete assignments that give you a head start on degree courses.

    Frequently Asked Questions:

    • Do I need to apply for admission to the Master of Computer Science in Data 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.
    • How do I get started? You may either apply and commit to the full Master of Computer Science in Data 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 in Data 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.
    • Is financial aid available? Coursera financial aid is available for the Specializations component of the program. Domestic students may qualify for Federal Student Aid, since the Master of Computer Science in Data Science, like all Illinois degrees, is accredited by the Higher Learning Commission.
    • I’m not interested in the full Master of Computer Science in Data Science -- can I take just one or two Specializations or courses on Coursera? Yes, each course or Specialization is available separately.
    • How do I earn credit from 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).
    • Do I have to pay for the entire degree upfront? 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.
    • What topics does the Master of Computer Science in Data Science cover? MCS-DS topics include data visualization, machine learning, data mining, cloud computing, statistics, and information science.
    • What is the Online MCS-DS? The Online MCS-DS is a professional, non-thesis, Master of Computer Science degree that requires 32 credit hours of coursework. Students can complete the eight courses required for the Online MCS-DS 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.
    • What is the MCS-DS? The MCS-DS is a focused track of the Online MCS whose requirements are fulfilled by courses in Data Science. A professional coursework-based degree program, the MCS-DS builds expertise in core areas of computer science like data mining, machine learning, cloud computing, and data visualization, in addition to building skills in statistics and information science.
    • What will appear on the diploma or transcript? The coursework for both the Online MCS and the MCS-DS track satisfies the requirements for our Master of Computer Science degree, so the diploma and the transcripts will only indicate “Master of Computer Science”. (The diploma will not mention the online mode of delivery, or data science.)
    • How is the Online MCS-DS offered? The Online MCS is a 100% online degree offered through the Coursera MOOC platform. To satisfy the degree requirements, students will complete 8 University of Illinois credit-bearing courses, with each course representing 4 credit hours (for a total of 32 credit hours). Each MCS-DS credit-bearing course is offered on a semester schedule (fall, spring, summer). Each course may run as long as the full 15 weeks available in a semester, though some courses may be shorter.
    • How is an Online MCS-DS course offered using the Coursera MOOC platform? Each credit-bearing semester-based Online MCS-DS course consists of two shorter 4-6 week Coursera MOOC courses plus additional credit-bearing components such as exams and/or projects. The two Coursera MOOC courses provide the lecture and lesson videos of the Online MCS course, as well as peer and auto-graded quizzes and assignments.
    • How are Online MCS-DS courses different than typical Coursera MOOC courses? The credit-bearing components for each Online MCS-DS course provides the ability for University of Illinois faculty and staff to assess work submitted in addition to the requirements of the Coursera MOOC courses. Faculty and staff provide guidance, advice, and feedback on submitted assignments, projects, and exams to students registered for University of Illinois credit.
    • I completed a Coursera Specialization. Will I earn graduate credit at the University of Illinois? Completion of Coursera MOOC courses/Specializations associated with the Online MCS-DS program by itself will not earn graduate credits from the university toward the degree. Students must be registered in the University of Illinois credit-bearing semester-based Online MCS-DS courses to earn graduate credit.
    • Are students expected to be proficient in a particular programming language? Students are expected to be proficient computer programmers to be admitted to any Master of Computer Science program. At the Masters level, students are expected to learn new programming languages on their own as needed, to develop the skill of using the appropriate programming tool to solve a particular problem. Each of the courses will have specific programming language requirements. Applied Machine Learning requires students to be proficient in the R programming language, whereas Statistical Programming in R is also based on the R programming language but provides an introduction to it. Cloud Computing Concepts requires students to be proficient in C++ programming to write low-level kernel functions, whereas Text Information Systems requires students understand enough C++ for high-level scripting calls of library functions that perform the low-level operations. Cloud Computing Applications can be completed using Python, but Java is encouraged as it is the primary language used for production cloud application programming. Data Visualization uses JavaScript programming, but provides students with tutorials and time to learn JavaScript before it is used in the course. Many of the other courses use higher level scripting languages like Python.
    • What if my undergraduate GPA is less than 3.0 (on a 4.0 scale)? University campus policy requires a GPA of 3.0 (on a 4.0 scale) for the last two years of undergraduate study for admission to any graduate program, but students admitted for the MCS degree typically have a GPA in excess of 3.2. The admissions committee will review applications with borderline GPAs which otherwise have a record of exceptional achievements. However, the likelihood of applicants with a GPA less than 3.0 being admitted to the MCS-DS program is expected to be low due to the competitiveness of the applicant pool and cohort size. Applicants who do not meet the minimum GPA requirements for this program are encouraged to make a realistic self-assessment before submitting an application.
    • When do Online MCS-DS classes start? Online MCS-DS classes follow the standard academic calendar at the University of Illinois at Urbana-Champaign.
    • What classes are offered for the Online MCS-DS? A list of courses for the MCS-DS is available here.
    • Will non-degree graduate students be able to take Online MCS-DS courses? Online MCS courses can be taken by non-degree students, but registration will be limited to the remaining capacity after Online MCS-DS students have been registered.
    • Do international students in this program receive an I-20? No. All requirements in the MCS-DS program are satisfied online. Students are not required to arrive on campus to meet any degree requirements. As such, no I-20s are issued.
    • How can I get more information about the Online MCS-DS? Sign up for updates by completing Coursera's Interest Form for the Online MCS-DS. For specific questions about the Illinois degree options, email online-mcs@cs.illinois.edu.
    • I have reviewed all information on the website and have remaining questions. Can I speak with an advisor? Please review all information available on our website. You can also email us at online-mcs@cs.illinois.edu. An advisor will be available online every Friday (other than campus holidays), 11:00 AM - 12:00 PM U.S. Central Time to help answer your questions.
    When we talk about data science, we mean the study of structured or unstructured data. In principle, data science was most widely used in the marketing and governance industry. Now data is a fundamental part of science like machine and deep learning, business and artificial intelligence, big data. etc.
    The study of data science is extremely interesting, on the edX platform you will also learn about emerging disciplines and directly related to the world of databases. Some of these specialties are: data mining, data visualization, data analysis or "data analysis", data processing and in general everything related to science related to the handling of large volumes of data. As you will notice, this subject offers a lot of material to cut, data science is a fundamental ingredient and basis of other sciences such as machine learning or machine learning and even artificial intelligence and big data.
    Learn with our free online courses and from the best universities worldwide, and leading professionals in the industry. edX offers you the necessary tools to become a comprehensive professional. There are two advantages that we can't stop talking about when we refer to our free online courses. The first advantage is that you can take each course at your own pace, and the second is that each of these introductory courses are specifically designed to help you learn fully and according to the demands of today's market. Take online courses on related subjects such as Excel for business and even on advanced technological subjects such as deep learning or deep learning and its relationship with the world of data science. With edX,
    The demand for data scientists has grown exponentially during the last 10 years and with it the different nuances and skills required for its development. These professionals solve complex problems derived from reading and exploratory analysis of large amounts of data. The value of their work lies in making the right decisions of the company. Developing your experience in data science can significantly improve your CV and open doors to highly paid industries such as business intelligence or business intelligence, among many others. A data science expert can work in many types of organizations to industries and there are thousands of job opportunities available worldwide. Becoming a data scientist has never been so easy,
    Data science has critical applications across most industries, and is one of the most in-demand careers in computer science. Data scientists are the detectives of the big data era, responsible for unearthing valuable data insights through analysis of massive datasets. And just like a detective is responsible for finding clues, interpreting them, and ultimately arguing their case in court, the field of data science encompasses the entire data life cycle.
    That starts with capturing lots of raw data using data collection techniques, and then building and maintaining data pipelines and data warehouses that efficiently “clean” the data and make it accessible for analysis at scale. This data infrastructure allows data scientists to efficiently process datasets using data mining and data modeling skills, as well as analyze these outputs with sophisticated techniques like predictive analysis and qualitative analysis. Finally, these findings must be presented using data visualization and data reporting skills to help business decision makers.
    Depending on the size of the company, data scientists may be responsible for this entire data life cycle, or they might specialize in a particular portion of the life cycle as part of a larger data science team.
    The most difficult step of all tasks is when you have no idea where to start. This article describes a short and direct learning path to start building your skills in the field of data science. The recently launched Big Data University Data Science Fundamentals Learning Path guides you through short, free online courses that prepare you to earn your IBM Data Science Foundations Level 1 and Level 2 badges to show off your new skills!
    Whether your background is in computer science, psychology, statistics, English, or otherwise, the valuable ability to analyze and understand data can put you in a good position in your current job, or the next. And, it is never too early to start. Increasingly, elementary schools are introducing students to concepts and tools to prepare them for their first job and business opportunities. The data science profession is in high demand, and has become the top job in many surveys in terms of wages (see Related Topics below).
    Big Data University is an initiative of the IBM community that started in 2010. Big Data University has more than 500,000 registered students and provides comprehensive learning paths for the areas of data science, big data and analytics, to care from a community of skilled open source data professionals. What's more, each BDU learning path offers an IBM badge after passing the first course of the path.
    BDU courses are short by design. They follow the "5 x 5" rule:
    • The learning routes cannot have more than 5 courses.
    • Courses cannot last more than 5 hours.
    • Courses cannot have more than 5 modules.
    • The modules cannot include more than 5 videos.
    • Videos cannot be longer than 5 minutes.
    This structure is ideal for busy people, like you, who want to learn small parts of the material at their own pace. It also forces BDU instructors to present the material in a compact way.
    Now get started with Big Data University on this free and simple data science learning path!
    This course uses an interview-style approach to teach the history and basics of data science. Taking Data Science 101 is like watching a documentary or a movie trailer. This course is one of BDU's most popular, with over 10,000 students enrolled just one month after its publication!
    So sit back, relax, take the course, and earn your first IBM badge from Data Science Foundations Level 1 ! Add the badge to your CV, and share it on LinkedIn and other social networks.

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