Our free video course Campaign Response Testing is no longer published on Udemy. It remains available for free on YouTube with all source code available from GitHub. I’ll try to correct bad links as I find them.
Please read on for the reasons.
Udemy recently unilaterally instituted a new policy on free courses: “When a free course has a Recent Review Rating less than 4.1 and is flagged with a ‘high degree of confidence’ the course will be hidden from Udemy’s search.”
Campaign Response Testing is a free course with an all-time average rating of 4.14 and a recent rating of 3.85. We have kept the code up to date and answered student questions (there was no backlog of student questions).
Obviously others should have opinion of our public work (which may or may not be good). And we are keeping the course up for free with no-sign up necessary on YouTube (as we in no way want to hurt or inconvenience students).
But I do have an issue with Udemy’s new system: it is completely vulnerable to griefers and spammers. Accounts with “no skin in the game” (having paid nothing, possibly not even have watched the course, and without having to leave any review text in addition to the “high degree of confidence” star rating) can belittle free courses at will and in bulk. Currently there is no effective dispute mechanism (other than superficial palliatives such as: “answer student questions”), and like all lop-sided “fights against semi-anonymous trolls” it would be a pointless effort anyway. I understand the desire to increase the quality of free content (it is Udemy’s “introduction”) but I feel the introduced system would obviously be unworkable even before it was introduced.
So with hopefully no harm to our subscribers I am un-publishing the course. As is the case with Udemy policy anybody already subscribed should continue to have access to the course through Udemy. And as I have said: we have long sense ported the entire free course to YouTube and Github for free and login-free sharing.
Data Scientist and trainer at Win Vector LLC. One of the authors of Practical Data Science with R.