Because data science has a strong emphasis on math, statistics and computer programming, master's degree programs in data science generally require that students have undergraduate coursework in those areas. Specific requirements will vary depending on the program, but students in a data science master's degree program usually have a strong foundation in at least some of those subjects.
Master's in Data Science Undergraduate Requirements
Each program will vary in the specific education it requires of applicants. It will depend on the focus and competitiveness of the program. Some universities may ask that applicants' bachelor's degrees be in STEM subjects: Science, technology, engineering or mathematics. Others may not specifically require it, but say that their undergraduates generally have backgrounds in those areas. Depending on the focus of the program, some may accept students from business backgrounds as well, like economics, psychology or social science. Overall, schools are looking for students with quantitative skills, so look for subjects that give them that background. Schools may ask for a certain overall undergraduate GPA, usually a 3.0 (B) or above. However, some schools may specify they usually accept students with even higher GPAs.
Master's in Data Science Specific Prerequisite Course Requirements
Besides the general bachelor's degree area, schools generally require specific coursework to have been completed before the beginning of the program. Some programs may even set certain grade requirements. The specific courses and number of credits schools ask for depend on the program.
Note that some schools may also allow relevant work experience to show proficiency in these areas, as opposed to college coursework. Some schools may also accept students on a contingency basis if they complete prerequisite courses before starting the master's program.
Schools generally ask for college-level calculus. It's common that they ask for two semesters, in Calculus I and II, but Calculus III is even better. Universities want students to have a knowledge of series, integrals, derivatives, limits and more. Specific programs will be able to provide detailed information about the knowledge students should have.
Programs usually require at least one semester of linear algebra. The specific topics that schools may be looking for include matrix manipulation, inverse matrices, vector spaces, linear transformations and more.
Again, schools may vary in the specific computer programming requirements. Some expect at least one introductory course. Others expect proficiency in at least one language. Languages that students can know include C++, Java, Python, R, Matlab, Ruby and more.
Schools also generally want a background in some statistics. Some ask for an introductory course, others ask for at least two courses. Topics that students may be expected to know related to statistics are regression analysis, histograms, probability modeling and more.
Other Application Requirements
Along with meeting the education and coursework prerequisites, applicants will generally need to submit two or three letters of recommendation from professional or academic sources, university transcripts, a resume and statement of purpose about why entering the program will help their careers or a similar topic. As far as graduate school entrance exams, some require GRE or GMAT scores and others don't. It depends on the school. Some programs don't require the exams but say that good scores can help applicants, especially if their GPA or other experience is lacking.
Overall, while specific prerequisites vary by program, strong candidates generally have a background in some kind of math, science, technology or engineering. They have taken prerequisite courses in calculus, linear algebra, statistics, and computer programming, and have an undergraduate GPA of at least 3.0.