edX: HarvardX Data Science - Probability Review

Data Science: Probability is the third course in the 9-part data science professional certificate series offered by Harvard on the edX course platform. The covers the basics of probability from a conceptual perspective and uses it as motivating topic teach students more about R. Since this course is part of a larger series, it is recommended to take the first two courses ion the specialization first so that you have the expected background in R. As with the other courses in the series, grading is based entirely upon a handful of programming problem sets administered through DataCamp, a web-based data science programming and learning platform.

Content in Data Science: Probability is split into 4 main sections: discrete probability, continuous probability, random variables and sampling methods and a short final section called "The Big Short" that explains how misguided assumptions contributed to the financial crisis of 2007-2008. Specific topics covered include: probability distributions, independence, combinations and permutations, probability density, random variables, the central limit theorem and Monte Carlo simulation. As a short course that is part of a professional education series, it focuses on conceptual understanding and practical applications in R while eschewing mathematical detail. That said, the lectures are well made, the instruction is clear and the lectures frequently use R code to illustrate concepts. The DataCamp assessments give you a chance to get practice with working with topics presented in lecture right away. The programming exercises could sometimes benefit from instructions that are a little more precise, but you can always get hints or view full solutions at the cost of points if you get stuck.

Data Science: Probability is a good high level introduction to probability geared toward those who have little to no experience with the subject and those who want to learn the basics of working with probability in R. Keeping the content focused on conceptual understanding and applications in R was the right decision because it is not possible to cover a topic like probability in depth in a course this short. Thus far the Harvard Data Science series has done a good job keeping content suitable for beginners and avoiding the pitfall of delving into content beyond its stated prerequisites. If you're interested in a mathematically rigorous and thorough introduction to probability, check out MIT's Introduction to Probability - The Science of Uncertainty, which is also available on edX.

I give Data Science: Probability 4 out of 5 stars: Very Good.