Top data science degrees, designed to fit your life
Receiving a degree in data science can open a path to a career in many fields. Whether you are looking to get your bachelor’s degree or advance your career with a data science master’s degree, you can find affordable online data science degrees from top universities offered on Coursera.
University of Illinois MCS-DS Student
We partner with leading universities to deliver the world's best online data science degree programs.
You don't need to quit your job or move to a new city to earn a top university degree in data science. Learn from the same professors and graduate with a high-value credential from the same university. Choose from a wide variety of online data science master’s degrees in some of today’s most in-demand fields, like a master's in data science.
Earn a high-stature data science degree for much less than similar on-campus programs.
We partner with top universities to create affordable learning programs that make data science degrees more accessible for everyone. With tuition well below most on-campus degree programs, online data science degrees on Coursera are designed to allow students to invest in their education and increase their earning potential post-graduation. Learning skills in data mining, cloud computing, data visualization and machine learning, you will be able to continue your job while earning your degree from a leading university. Financial aid is available for qualified students.
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Courses, Specializations, or MasterTrack Certificates that are part of degrees allow you to start learning right away, so you can make progress on your own schedule. If you are admitted to the full program, your completed courses count towards your degree learning.
Benefit from team-based learning and live expert instruction.
Online data science degrees on Coursera are powered by technology that helps you spark meaningful connections with faculty and your peers. Throughout the program, you may attend online lectures from anywhere and interact directly with professors and classmates. On every step of your learning journey, you’ll have access to a dedicated online student support team. Get help to resolve sticking points so you can master new concepts and gain data science.
The cost, the flexibility, and the material — you put all that together, I think it is a phenomenal option.ASHISH KUMAR, MCS-DS GRADUATE
University of Illinois iMBA Student
University of Illinois MCS-DS Student
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University of Illinois MCS-DS Student
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University of Illinois MCS-DS Graduate
John C. Hart is a Professor of Computer Science and the Director of Online and Professional Programs at the University of Illinois at Urbana-Champaign. He received his Ph.D. in Electrical Engineering and Computer Science from University of Illinois at Chicago in 1991. He has taught and researched computer graphics and data visualization for over 25 years. His research has been supported by Adobe, DARPA, Intel, Microsoft, NSF, Nokia and NVIDIA, and has resulted in over 125 papers, patents and videos.
Professor Hart teaches the Data Visualization course in the Illinois Master of Computer Science in Data Science.
A Data Science Master's degree is relatively new an graduate program that combines core concepts from mathematics, computer science, statistics, and information science to leverage insights and help data scientists improve operational and business processes. A Data Science masters is best positioned for someone who is interested in furthering their data science career, or interested in building or expanding skills in machine learning, cluster analysis, databases, data visualization, statistics, data mining and more.
Coursera's Data Scientist Allie says: "I took on an entry-level role that had flexibility in the job description. I was not expected to be a data expert, by any means. But with the flexibility, there were tasks that really piqued my interest. From there, I could move from operations analytics to other functions."
You can learn data science anytime and anywhere in the world – All you need is an internet connection.
For students that go through data science degree courses on Coursera that are accredited by our university partner, all of the content is created by university faculty members who are subject matter experts. Your degree will be conferred and accredited by the universities themselves.
The “Launching and Advancing Your Data Science Career” webinar, aired on June 24, 2020, discusses why a future in data science might be the right move for you. The webinar features Allie Rogers and Marianne Sorba, Coursera’s very own data scientists, and covers their experiences in their respective Masters of Data Science programs, their different journeys into the data science field, projects they’re currently working on, and critical skills needed to succeed at their roles. The webinar is hosted by Diana Sunshine, Senior Degrees Marketing Manager at Coursera, and Miguel Alvarez, Head of Enrollment at Coursera.
These days, it's not a requirement. When I joined data science, I would not have considered myself to have a background in mathematics. I studied economics and had been in the workforce for a while, and it wasn't something that I had really been using. I do see plenty of other people without a background in math in the field. The skills that I was focusing on developing at first (that I really needed) to get over the hump and be a viable data scientist were mostly in computer programming.
Typically, in a master's of data science, you will cover the math that's needed in data science. This involves basic statistics, the math behind optimizing algorithms. It helps to have a background in mathematics, but it’s not a requirement.
R is more useful than Python in data analysis and data visualization. It's also useful for traditional statistical models. Any type of regression is easier to do with R. Python is the tool for anything related to machine learning. It's open source, so there's always going to be new people building useful libraries. There's a machine learning library called scikit-learn that can accomplish many of the most common machine learning models. The breadth of what you can do with Python is broader.
Both have a lot of strengths, but it's good to start with Python if you're not sure what type of data scientist you're going to become yet.
I took on an entry-level role that had flexibility in the job description. I was not expected to be a data expert, by any means. But with the flexibility, there were tasks that really piqued my interest. From there, I could move from operations analytics to other functions.
You can learn anytime and anywhere in the world – All you need is an internet connection.
I'm not an expert in medicinal chemistry, but I would say that anywhere we're able to collect data, data science can find unbiased insights that humans would be able to find themselves. Many times, the scale of the data cannot be processed by just one human being. It can also detect patterns and be able to make smart decisions on really complex data.
I have seen, for folks taking our data science degrees, that a lot of them already have computer science backgrounds, and they just need that extra push in data science, so they really are taking the courses to gain the skills and prove they can be hired in these roles.
In my MCS-DS program right now, you can focus on the data science track. Those with backgrounds in software engineering who may not have a background in data are really focused on beefing up their data skills, like building data visualization and data analysis projects in a portfolio that they can also share on GitHub.
Data mining is a subfield of data science. Data mining is related to data engineering – It's how someone works with the data to make it clean and accessible. On top of that, you can do data analysis and machine learning. In order to successfully do machine learning though, companies need to invest time and effort on how to make data accessible, which includes building data pipelines.
For students that go through courses on Coursera that are accredited by our university partner, all of the content is created by university faculty members who are subject matter experts. Your degree will be conferred and accredited by the universities themselves. It will not say "online" – It will say the degree you received.
Coursera offers online Master’s degrees and Bachelor's degrees in Data Science, Computer Science, Information Technology, Engineering, MBA, Accounting, Entrepreneurship, and Public Health. If you are still evaluating a full degree program on Coursera, you might be interested in a MasterTrack Certificate. Data Science MasterTrack Certificates that are part of degrees allow you to start learning right away, so you can make progress on your own schedule. If you are admitted to the full program, your completed courses count towards your degree learning.
Discover financial resources to help fund your degree, and get the support you need to successfully pursue your learning goals.