University of Michigan
#1 graduate program in Information Systems (Library and Information Schools), U.S. News & World Report (2017)
Overview An applied, skills-based program in data science developed by world-class faculty at the top-ranked University of Michigan School of Information
This program is for Learners from a broad range of backgrounds including those from the sciences, social sciences, or professional schools.
Degree courses & Specializations you can start right now The Python 3 Programming Specialization teaches the basics of programming in Python 3.
The Statistics with Python Specialization covers beginning and intermediate concepts of statistical analysis using the Python programming language.
Next application deadline is October 1st, 2020
University of Illinois at Urbana-Champaign
#5 ranked CS program in the U.S., U.S. News & World Report (2018)
Overview 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
This program is for Professionals who want to use big data to understand the world, discover new insights, and optimize their decision-making.
Degree courses & Specializations you can start right now
Next application deadline is October 15th, 2020
Imperial College London
#9 ranked university in the world, Times Higher Education (2019)
Overview One of the world’s first online Master’s in Machine Learning from one of the best-ranked universities in the world.
This program is for This degree meets the needs of students with multiple backgrounds -- both students just starting a career in data science, and those already working in roles such as senior data analysts, bioinformatics scientists, statisticians or business analysts.
University of Colorado Boulder
#14 ranked Applied Math program in the U.S., U.S. News & World Report (2020)
Overview An interdisciplinary, applied data science master’s degree with no application.
This program is for Anyone who is interested in the field of data science, no matter your academic background.
Admissions Requirements Performance-based admissions means there are no prerequisites or an application. Take a series of area-specific exams, earn a B average or better, and you will be admitted into the degree. Learn and earn credit without needing to wait 6 months while your application is being completed and reviewed.
National Research University Higher School of Economics
#8 Russian University on *QS Top University* rankings
The first fully online Master of Data Science from a top-10 Russian university, featuring applied projects and faculty with industry expertise from leading companies from Russia and beyond.
Universidad de los Andes
#8 Times Higher Education Latin America (2018)
The MIAD, a Spanish-language degree, designed to train students to become data-driven leaders and decision makers. The curriculum will offer a blend of mathematical modeling, organizational management, and IT.
This program is for
Non-STEM professionals with basic programming and statistical knowledge.
Expected to begin admissions by the second quarter of 2021 and classes start in August 2021 after official approval from the Colombian Ministry of Education.
Data scientists are urgently needed in many industries that are vital to our global economy, such as agriculture, finance, healthcare, manufacturing, technology, and transportation. With Coursera, you can become a Data Science professional and earn your Master’s degree from a top university. Data Science degree programs on Coursera feature hands-on learning, peer-to-peer support, and the same professors that teach degree courses on campus. You’ll learn ways to derive insights from massive datasets as you learn cutting-edge tools and methods from world-class faculty.
Data science is one of the most in-demand career fields in computer science. According to LinkedIn, job openings increased 56% over the past year. These big data detectives unearth valuable insights through analysis of massive datasets. As demand for data-driven decision makers continues to grow, it is projected that by 2020, there will be a 15% growth in data science careers. According to Coursera’s analysis of global skills, the most sought-after data science skills include math, statistics, machine learning, data management, statistical programming, and data visualization.
University of Illinois MCS-DS Student
Boost your career with a master's in data science Business Insider cites data scientist as the highest paying job for college graduates, at $95,000 per year. PayScale indicates that the average salary of an MCS degree-holder is about $18,000 more than those who only hold a bachelor’s degree in computer science. The projected 5-year growth for data science salaries ranges from 14 to 28%.
Coursera offers data sciences degrees from leading universities around the world: University of Illinois Champaign Urbana, University of Michigan, Higher School of Education from Russia, Imperial College of London and University of Colorado Boulder. These degrees from top-quality programs teach the underlying fundamentals that help students pursue a long-term career, no matter how their field changes over the years.
Transform your career with a master’s at an accessible price. Cost of higher education has made education out of reach to many people around the world. Although education programs focused on data science often boast about six digit data scientist salaries, cost is still one of the primary decision factors for many students considering degrees. Degree programs offered on Coursera often times are as little as half the cost as their on-campus counterparts.
With 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. In as little as three years, you will be ready to accelerate your career in data science.
Try your first course risk-free & start working towards your Data Science degree today. Start learning right away with an open degree course, Specialization, or MasterTrack™ Certificate and make progress on your own schedule. If you are accepted into the degree program, your completed work can count towards your degree. Select one of the Master’s programs above and try a Data Science online course that you can start today.
Learn data science skills on a platform designed to engage students. Data scientists learn by doing. While theory is an important foundation to build when creating powerful tools that manipulate large data sets, students must be engaged and practices as they enter the field of data science. In order to understand everything from experiment design to creating more complex models for use in predictive analytics & scoring engines, data science students must be working in platforms that simulate real data science environments.
Degrees offered on Coursera in data science often leverage applied projects that take advantage of programming environments data scientists use professionally every day. With forums on the platform, Slack, and Zoom for office hours & ad-hoc meetings, students have a number of resources that help drive an engaging data science learning experience.
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
Average work experience
University of Illinois MCS-DS Student
1st year student retention
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.