Data science is one of the fastest-growing and most in-demand fields in the U.S. In fact, between 2021 and 2031, the U.S. Bureau of Labor Statistics projects that the demand for data scientists will grow by 21%—much faster than the average for all jobs. And data science was the most sought-after tech skill in 2021, DevSkiller reports.
“The rise in popularity of data science comes as little surprise given how valuable data has become to companies across the globe,” according to a report from DevSkiller, a tech interview and skills-building platform. “Companies are spending big on building the right teams of data scientists who can help them grow more dynamically.”
Speaking of big money, the Bureau of Labor Statistics reports the median data scientist salary to be $131,490, with the highest 10% of data scientists earning more than $208,000. The Bureau notes, however, that many entry-level data science positions require a master’s degree. Still, how are data scientists are earning nearly four-times the amount of workers who hold only a bachelor’s degree?
“It’s the combination of rapidly growing demand and very small supply,” Michael Yoo, Skillsoft’s general manager of technology and developer portfolio, previously told Fortune. Skillsoft offers online training and courses on tech subjects. HackerEarth also reports that data science in 2021 was the “domain that is most coveted by both students and professional developers.”
While some data science roles require—or highly value—a master’s degree, many top universities offer courses for professionals to get acquainted with the field. Fortune has compiled a list of seven online courses for prospective data science workers to check out before committing to a data science master’s program.
Data science applications often require understanding relationships between two variables, and linear regression is commonly used to quantify that relationship, according to Harvard University. The school offers a free online course called Data Science: Linear Regression, which is designed to teach participants how linear regression was developed and how to examine relationships between variables. This intro-level course is self-paced and takes eight weeks to complete, committing one-to-two hours per week.
Participants can also take the course as part of a professional certificate in data science program, which can be completed for $790.80. The professional certificate program includes nine courses all taught by Rafael Irizarry, a biostatistics professor at the Harvard T.H. Chan School of Public Health and the Dana-Farber Cancer Institute.
Ethical concerns have increasingly become a part of data science curricula as these professionals gain more access to collecting and analyzing user data. While data science programs have started to place more focus on the topic of ethics, companies seemingly continue to place more focus on tech developments that increase the speed and access to user data, according to previous Fortune reporting.
The University of Michigan offers a free online Data Science Ethics course, which focuses on privacy and informed consent. The course is taught by H. V. Jagadish, an electrical engineering and computer science professor at Michigan. It takes four weeks to complete the course, which requires about three-to-four hours of commitment each week. If a participant wants a certificate they can share, then they can pay for a verified track, which costs $49.
The University of California—Irvine, which Fortune ranks as having a top data science master’s program, offers a four-course online data science fundamentals specialization, which covers introductory data science topics. The first course in the specialization is Intro to Analytic Thinking, Data Science, and Data Mining, which serves as an introduction to the field and profession.
Students also review the types of business problems that can be solved using data science and the ethical considerations necessary when working with data. This course takes about seven hours to complete over the course of four weeks. The course also includes an overview of data analytics and is taught by Julie Pai, assistant director of technology programs at UC Irvine, and Dursun Delen, a data science instructor with the school.
Rarely do data science exercises go completely to plan, according to Johns Hopkins University, which Fortune ranks as having a top data science master’s program. Data Science in Real Life, a free online course through Johns Hopkins, however, helps participants learn what “perfect” data science experiences can look like, while also looking at the downfalls and challenges that data scientists face along the way.
Participants also learn about A/B testing, managing data quality, and bias and confounding. The course takes about seven hours to complete, and is taught by three professors from Johns Hopkins’ Bloomberg School of Public Health: Brian Caffo, Roger D. Peng, and Jeff Leek. Data Science in Real Life can be completed in one week, and is part of Johns Hopkins’ online executive data science specialization.
Machine learning, which allows computer systems to learn and adapt without instruction, is a growing field within artificial intelligence—and machine learning engineers are in high demand, according BuiltIn, a tech publication. Columbia University’s free online course, Machine Learning for Data Science and Analytics, offers an overview of what machine learning is and how it is related to data science. Participants also learn how to work with data, find patterns within data, and use algorithmic techniques to sort and search data.
The self-paced course takes about five weeks to complete with seven-to-10 hours of work per week. Machine Learning for Data Science and Analytics is taught by three Columbia University computer science professors: Ansaf Salleb-Aouissi, Cliff Stein, and David Blei. Students can pay $99 if they’ve like unlimited access to course materials after completing the class.
The Massachusetts Institute of Technology, renowned for its tech-focused research and curriculum, offers a free online course called the Introduction to Computational Thinking and Data Science. The course is offered through MIT’s open courseware platform, and was originally taught and recorded in fall 2016. Students can access the course lectures, syllabus, lecture slides and files, assignments, and software all through this platform and lead themselves through the class for free.
Students should typically first take Introduction to Computer Science and Programming in Python to learn how to program. The intro to computational thinking and data science course, however, helps students learn how data and computer science can help solve problems and prepare students to complete programming projects.
In order to succeed in data science courses, math skills are required. Duke University’s free online course Data Science Math Skills covers topics including set theory, number lines, algebra, summation, and distance formulas, among other data science-related math. Some students also use it as preparation for Mastering Data Analysis in Excel, another free online course offered by Duke.
This beginner-level course takes about 13 hours to complete over four weeks, and participants can earn a completion certificate. It’s taught by Daniel Egger, executive in residence in Duke University’s master of engineering management program, and Paul Bendich, an assistant mathematics research professor at Duke.
See how the schools you’re considering fared in Fortune’s rankings of the best master’s degree programs in data science (in-person and online), nursing, computer science, cybersecurity, psychology, public health, and business analytics, as well as the doctorate in education programs MBA programs (part-time, executive, full-time, and online).
