Data Science
Data science Specializations and courses teach the fundamentals of interpreting data, performing analyses, and understanding and communicating actionable insights. Topics of study for beginning and advanced learners include qualitative and quantitative data analysis, tools and methods for data manipulation, and machine learning algorithms.
Earn Your Degree
Most Popular Data Science Courses
Applications for Michigan’s MPH degree are now open
Apply by May 1, 2020 to earn your master’s degree online from a top-rated program.
Join us April 14 to learn about reinventing business models from an MSIE professor.
Trending Data Science Courses
Most Popular Certificates in Data Science
Best of Machine Learning & AI
Top Rated Data Science Courses
Master Fundamental Math Skills and Statistics for Data Science
Becoming a Data Scientist
Data Science for Non-Practitioners
Skills you can learn in Data Science
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.
Computer science is one of the most common subjects that online learners study, and data science is no exception. While some learners may wish to study data science through a traditional on-campus degree program or an intensive “bootcamp” class or school, the cost of these options can add up quickly once tuition as well as the cost of books and transportation and sometimes even lodging are included.
As an alternative, you can pursue your data science learning plan online, which can be a flexible and affordable option. There are a wide range of popular online courses in subjects ranging from foundations like Python programming to advanced deep learning and artificial intelligence applications. Students can choose to get certifications in individual courses or specializations or even pursue entire computer science and data science degree programs online.
Best of all, these online courses include lecture videos, live office hour sessions, and opportunities to collaborate with other learners from all around the world, giving you the chance to ask questions and build teamwork skills just like you would on campus.
In today’s era of “big data”, data science has critical applications across most industries. This gives students with data science backgrounds a wide range of career opportunities, from general to highly specific. Some companies may hire data scientists to work on the entire data life cycle, while larger organizations may employ an entire team of data scientists with more specialized positions such as data engineers to build data infrastructure or data analysts, business intelligence analysts, decision scientists to interpret and use this data.
Some tech companies may employ much more specialized data scientists. For example, companies building internet of things (IoT) devices using speech recognition need natural language processing engineers. Public health organizations may need disease mappers to build predictive epidemiological models to forecast the spread of infectious diseases. And firms developing artificial intelligence (AI) applications will likely rely on machine learning engineers.
Coursera offers professional certificates, MasterTrack certificates, Specializations, and courses in data science from top universities like Johns Hopkins University, University of Pennsylvania and companies like IBM. Popular online courses for data science include introductions to data science, data science in R, Python, SQL, and other programming languages, basic data mining techniques, and the use of data science in machine learning applications.
More and more students are looking to pursue entire degree programs in data science online. There are several reasons for this, starting with cost: with Coursera's degree programs, you can get the same high quality education and the same diploma as your on-campus colleagues at a fraction of the cost. Flexibility is another big reason; particularly if you're already working full-time, the ability to pursue your data science education on your own time instead of having to take time off from your job is a huge advantage.
The popularity of data science courses on campus are also increasing the appeal of online courses. Many students who want to take these courses on campus find them overenrolled, or else so crowded that lectures are challenging to follow and access to faculty is lacking. Thanks to videos of classes, online students can watch lectures on their own time in a focused environment, and virtual office hours provide regular access to faculty. Online courses can thus make learning more accessible for aspiring data scientists.
Learning online doesn't mean sacrificing when it comes to the name on your diploma, either. Coursera currently offers data science degrees from top-ranked colleges like University of Illinois, Imperial College London, University of Michigan, University of Colorado Boulder, and National Research University Higher School of Economics.
