The topics covered in Data Science depending upon the level of the course i.e. whether students are enrolling for a basic course or a more advanced course. Basic courses generally introduce the student to concepts of statistics and probability, and then proceed towards preliminary hypothesis testing procedure such as t-test, z-test, ANOVA, F-test etc and finally advances to cause-effect modelling such as regression, factor analysis, logistic analysis etc.

Advanced courses, on the other hand, starts with regression analysis and then progresses to more complicated algorithms such as random forest, decision trees, Bayesian principles, collaborative filtering and so on.