Introduction to Analytics Modeling

I am about to complete the course as a verified learner, i found the course content to be very good and very well spread out.

Thumb's up-
->The details covered are very structured and well articulated,sometimes even some small tips from Prof Joel within the videos are very valuable to say the least.
->TA's associated with the program are very responsive and are more than willing to answer your doubts , i learned a lot from them .
-> Assignments and tests are usually very hard ,so its fun to look back and see the steep climb you made over the weeks

Thumbs down-
-> Video content for some weeks was very limited to only scratching the surface which caused a lot of alternate reading to get the concepts sometimes
-> The course assumes you have a decent knowledge of stats and R, (although a good effort is made by the teaching staff to upload help materials to bring people upto speed as a separate add-on part of the course)

Overall i would recommend this course to anyone who wants to build a solid foundation in analytics.

I just finished this course as a verified learner. The content is excellent (5 stars), but for two reasons my overall evaluation of the course is a 4 stars:

This is the first time this course is offered via edX, and there were many technical glitches. But course staff was very responsive, and I assume that these problems will be fixed in future versions of the course.

The course announcement wasn't clear about required knowledge and skills to take the course. Most homework requires proficiency in R.

A positive point was the very active Slack group of students, which helped a lot. (The edX forum, on the other hand, was difficult to use.)

Bottom line is, this course is extremely interesting, one of the best I have ever taken, very ambitious with the topics covered. You will enjoy the course if you have basic proficiency in R.

I found this course to be very well executed. While there were some technical difficulties at times but they were easily compensated by the ever responsive TAs, messaging board, office-hours etc.

The course does a great job of covering a lot of topics. Due to this reason some of the topics feel like glossed over but I guess that is more by design than overlook. If you are a beginner, then you will need to invest a lot of time reading material other than what is discussed in videos / assignments to get a decent understanding of the topics.

The course require familiarity with R. My R knowledge was rusty and hence I had to spend a lot of time for the first couple of assignments. I think it would be great if the course videos can spend some time in setting the expectations regarding the use of R in assignments.

Fantastic course! It was pretty challenging, it's an introductory course in that the professor touches on many different topics to give you a feel for the techniques needed to solve many types of problems, and the common terms and tools used. For further research you are expected to seek out more information, but they give alot of guidance to get you started on the process. Since the material alone is challenging though, and it would have been too much if it was my first encounter with R/python/machine learning. Definitely the stand out to me was the combination of homework, all problems with practical applications, and the 2x weekly TA sessions, with the first session explaining how to setup and think about the assignment, and the second session giving a breakdown of the solution. That by itself makes the notes for this class incredibly useful, and something that I'll refer to and build upon as I encounter these topics in other classes.