Coursera – an online education startup – has rapidly expanded its curriculum of statistics and data analysis courses. Today, there are already 33 modules directly linked to the field, excluding the courses where statistics and data science are solely used as a supportive tool (e.g. finance). These courses make use of multiple statistical software packages like Python, MATLAB and of course R.
I decided to make a list of all Coursera courses that use R as either their first choice, or as one of the many statistical software packages allowed to use by students to perform the homework’s assignment. Coursera does not publish all data on how many students enroll in their courses, but most (some?) courses reach well over a hundred thousand students each year.
To have some kind of indication of their popularity, I list below all courses using R ranked by the number of facebook likes:
Ranking | Courese title | Professor | University | Facebook likes | Tweets | |||
1 |
Social Network Analysis |
Lada Adamic | University of Michigan | 12000 | 3543 | |||
2 |
Statistics one |
Andrew Conway | Princeton University | 9600 | 1421 | |||
3 |
Computing for Data Analysis |
Roger Peng | John Hopkins University | 8500 | 1934 | |||
4 |
Data Analysis |
Jeff Leek | John Hopkins University | 5200 | 1408 | |||
5 |
Introduction to Data Science |
Bill Howe | University of Washington | 2600 | 1103 | |||
6 |
Introduction to Computational Finance and Financial Econometrics |
Eric Zivot | University of Washington | 2100 | 351 | |||
7 |
Mathematical Biostatistics Boot Camp 1 |
Brian Caffo | John Hopkins University | 1400 | 239 | |||
8 |
Statistics: Making Sense of Data |
Alison Gibs & Jeffey Rosenthal | University of Toronto | 1400 | 243 | |||
9 |
Asset Pricing |
John H. Cochrane | University of Chicago Booth | 855 | 102 | |||
10 |
Mathematical Methods for Quantitative Finance |
Kjell Konis | Columbia University | 635 | 92 | |||
11 |
Case-Based Introduction to Biostatistics |
Scott L. Zeger | John Hopkins University | 424 | 110 | |||
12 |
Financial Engineering 2 |
Martin Haugh & Garud Iyengar | Coumbia University | 109 | 13 | |||
13 |
Data Analysis and statistical inference |
Mine Çetinkaya-Rundel | Duke University | 80 | 18 | |||
14 |
Core Concepts in Data Analysis |
Boris Mirkin | Higher School of Economics | 77 | 15 | |||
15 |
Mathematical Biostatistics Boot Camp 2 |
Brian Caffo | John Hopkins University | 60 | 21 |
Given the unwillingness of Coursera’s search function, I had to manually draft the list above. Therefore, it is possible I overlooked some of the courses. Feel free to mention them in the comment section, and I will make sure to update the list. In case you are interested in taking (or teaching) interactive data analysis courses, make sure to have a look at our own educational startup DataMind.
While I expect that most of you are familiar with Coursera, for those who don’t a quick summary: Coursera is one of the leading providers of Massive Open Online Courses (MOOCs). Today they have more then 100+ institutional partners offering 500+ courses to over 5 million students worldwide. So despite being criticized by some, it is becoming more and more clear that they are here to stay.
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