The Best Statistics & Probability Courses for Data Science
The best online introductory statistics and probability courses for people looking to learn data science are the University of Texas at Austin’s “Foundations of Data Analysis” two-part series (“Statistics Using R” and “Inferential Statistics”).
The series includes two of the top reviewed courses available with a weighted average rating of 4.48 out of 5 stars over 20 reviews. It is one of the few courses/series in the upper echelon of ratings that teach statistics with a focus on coding up examples.
Foundations of Data Analysis – Part 1: Statistics Using R by the University of Texas at Austin on edX
Foundations of Data Analysis – Part 2: Inferential Statistics by the University of Texas at Austin on edX
A stellar specialization
Update (December 5, 2016): Our original second recommendation, UC Berkeley’s “Stat2x: Introduction to Statistics” series, closed their enrollment a few weeks after the release of this article. We promoted our top recommendation in “The Competition” section accordingly.
Based on a course that had a 4.82-star weighted average rating over 55 reviews, Duke University’s Statistics with R Specialization is another great option. The five-course specialization, which is relatively new, has a comprehensive syllabus with full sections dedicated to probability. There are only five reviews for the new individual courses, so their 3.6-star weighted average rating should be taken with a grain of salt.
Statistics with R Specialization by Duke University on Coursera
…which contains the following five courses:
Introduction to Probability and Data
Inferential Statistics
Linear Regression and Modeling
Bayesian Statistics
Statistics with R Capstone
Want more probability?
If you want to dive deeper into probability, opt for MIT’s “6.041x: Introduction to Probability – The Science of Uncertainty” instead of UC Berkeley’s probability offering above. MIT’s offering has by far the highest weighted average rating (4.91 out of 5 stars over 34 reviews) of any course/series considered in this guide. 6.041x is almost identical to MIT’s on-campus version. It covers more probability than a standard introduction to probability and statistics, plus it is longer (15 weeks) and more challenging than most MOOCs. (Via Class-central)
Introduction to Probability – The Science of Uncertainty by the Massachusetts Institute of Technology (MIT) on edX
Table of Contents
Why You Should Trust Us
About the Data Science Career Guide
Statistics AND Probability
How We Picked Courses to Consider
How We Tested
Why Target Coding?
Our Picks
A Stellar Specialization
Want More Probability?
The Competition
About Class Central Career Guides
Author Bio
The series includes two of the top reviewed courses available with a weighted average rating of 4.48 out of 5 stars over 20 reviews. It is one of the few courses/series in the upper echelon of ratings that teach statistics with a focus on coding up examples.
Foundations of Data Analysis – Part 1: Statistics Using R by the University of Texas at Austin on edX
Foundations of Data Analysis – Part 2: Inferential Statistics by the University of Texas at Austin on edX
A stellar specialization
Update (December 5, 2016): Our original second recommendation, UC Berkeley’s “Stat2x: Introduction to Statistics” series, closed their enrollment a few weeks after the release of this article. We promoted our top recommendation in “The Competition” section accordingly.
Based on a course that had a 4.82-star weighted average rating over 55 reviews, Duke University’s Statistics with R Specialization is another great option. The five-course specialization, which is relatively new, has a comprehensive syllabus with full sections dedicated to probability. There are only five reviews for the new individual courses, so their 3.6-star weighted average rating should be taken with a grain of salt.
Statistics with R Specialization by Duke University on Coursera
…which contains the following five courses:
Introduction to Probability and Data
Inferential Statistics
Linear Regression and Modeling
Bayesian Statistics
Statistics with R Capstone
Want more probability?
If you want to dive deeper into probability, opt for MIT’s “6.041x: Introduction to Probability – The Science of Uncertainty” instead of UC Berkeley’s probability offering above. MIT’s offering has by far the highest weighted average rating (4.91 out of 5 stars over 34 reviews) of any course/series considered in this guide. 6.041x is almost identical to MIT’s on-campus version. It covers more probability than a standard introduction to probability and statistics, plus it is longer (15 weeks) and more challenging than most MOOCs. (Via Class-central)
Introduction to Probability – The Science of Uncertainty by the Massachusetts Institute of Technology (MIT) on edX
Table of Contents
Why You Should Trust Us
About the Data Science Career Guide
Statistics AND Probability
How We Picked Courses to Consider
How We Tested
Why Target Coding?
Our Picks
A Stellar Specialization
Want More Probability?
The Competition
About Class Central Career Guides
Author Bio
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