Complete Course on A/B Testing with Interview Guide (Udemy.com)

There is no delving into the statistics and the interview questions are not answered. A lot of jargon is introduced at the end of the course in the mock interviews which isn't touched on during the course. We do not discuss choice of statistical test or exactly how to set up the tests in R - the code is provided but the choice of test and proper set up is assumed. Some important fundamentals are discussed, but if you want details on stats or randomization, this is not really the course for you.

This course gives a good high level overview of the topics described in the course description. The concepts are explained very clearly. The R code is an additional plus but could be improved. The course can also be further improved by going into more detail of some of the concepts, such as presenting the respective equations and explanations on how to calculate things by hand etc. The slides of the course are very nice. The idea of presenting mock interviews is innovative and nicely done. Overall I enjoyed the course, it complements well with other courses on Udemy on the topic of A/B testing.

As a UX/UI designer with a relatively small background in data science due to my experience in university, I found this course rather useful to understand the process of generating hyphotheses, calculating samples. Though the testing part was more difficult to me and even with some coding stuff, I wasn't very sure how can I replicate that even with some coding background in Python before, though I appreciate that this course has given me info about A/B testing platforms that might come useful in my future job as a UX/UI Designer.

Very engaging, structured, liked parts where there is music in the background of speech (it helps my brain concentrate and not loose the attention and desire to listen), cool examples, simple but at the same time fulfilling and helpful, love that all steps in examples are explained

A wonderful course to learn A/B testing. The most attractive merits of this course that I appreciate much: 1. This course provides not only theoretical setting of A/B testing, but it emphasizes on the business intuition and reasoning. And more, there are plenty of concrete business use cases and interview questions that make this course really helpful for practical purpose. Especially the interview question part, the answers are just perfect that they are very critical in logic and also practically strict to the point to solve real-world problems. 2. There are lectures that introduce multi-variate testing and multi-armed bandit testing that often are missed in other courses. For improvement of the course, I suggest: 1. There can be bonus lectures that go in-depth to multi-variate testing and multi-armed bandit testing. 2. Some optional bonus lectures can be considered to be added, taking a math-savvy approach, that provides a solid formulation of the problems in the mathematical language. (e.g. How do we derive the formula of the sample size calculation? I am a Statistics bachelor holder, for this part I completely know how to do; Moreover, multi-variate analysis is related to a Statistics subject - Experimental Design, Multi-armed bandit problem is classical in reinforcement learning, in fact these topics can all be taught using a rigorous treatment if we want.) 3. There can be a bonus lecture that explains some R codes and libraries used.

It was very good and covered all the key aspects of A/B testing and the statistics involved. For someone who is new to stats I found some of the concepts difficult to get my head around and will probably have to go over some of it again but it provided a good foundation.

The concepts are explained in an easy to understand format initially. Although I did feel topics were a little short on coverage in later chapters. I noticed, there are only 28 questions asked in this course and barely 1 or 2 have been attended to by the trainer. I would have really appreciated more answers to the interview questions and elaboration on how to solve for things like network effects and seasonality etc.

I finally learned AB testing end-to-end. This course as set me up for success. To the extent that it has helped me prepare for a product analytics interview. The fact that multivariate testing was not part of this course was good. There is no point in learning advance topics in something if You have not master the basics in my honest opinion. If you want learn AB testing this is course for you. The instructor takes time to provide the “Why” the theory, before the “What” which is the practical application. You may need to Google a little to get more insight if something does seem clear for example I needed another source to understand MDE in laymen terms. But , that was me since I wanted go deeper into the MDE topic. With that said, it took me all of 5 mins to search, read and understand the topic to the extent I can teach it myself. This is when you know someone taught you something - when you can teach it someone else.

This is introduction course on A/B test for me. Instead of running here and there and finding information in bits of pieces, this course gave me complete outlook about A/B test and area and tools I will use to enhance my skill in A/B testing. I would appreciate if it include the model answers on questions mentioned on Part 24. Overall good course for me.

This is a really good course and the instructor is clearly an expert as well - I think - a good teacher. There's a couple of places I think could have been a little better... * Several third party testing platforms were mentioned. It might have been nice to have had a separate lecture just looking at some of those. I understand features/benefits of such products can change fast, but a quick look might have been nice. * When we got to confidence intervals and formulas, some charts/formulas were put up, but not really picked apart as well as I think they could have been. We can all read a formula, but understanding really how/why each factor is in there could use more explanation. Same with significance level. Still, I end where I began... solid intro course. Solid instructor. (And just by the way, if you're new to R and decide to install it, you may need to play with getting some of the libraries/packages to install. They didn't go in cleanly for me on a Mac and required some Googling. So if things don't work perfectly straight away, just maybe try to manually install a package or library.