I was a bit disappointed by the notebooks of week3: missing some details and explanations for me.

please better explanation of python videos

In my opinion, the course does not worth. I just complete it, as I came from the first two courses and I wanted to complete all the specialization (and I still had some days untill the deadline of the fee).

The first week is very basic. Week two, could be the most usefull if they had develope the maths behind fitting, not just a conceptual explanation. And finally weeks three and four, in my opinion, are out of the level of the course; I can't understand why to move to multivelel or Bayesian, if the basic fitting of Week2 has not been explained. In all the course, just concepts are explained, not the maths to understand in detail.

Moreover, I found too many extern lectures, apps or interviews that add little to the course.

The quiz, as in the previous course should be re-thought, I don't think are the best evaluation method. As for example, you can have wrong answer just not for running the code in Jupyter Notebook but in Spyder. Moreover, the quiz from weeks 2 and 3 about Python are ridiculous, you just have to run a code already written by the teaching stuff.

Good job in covering the initial models, and then above average when going into the multi-level modeling, but pretty disappointed on the marginal and the bayesian. Bayesian videos started out well, but really felt superficial when it was all done. With all of the courses in this specialization, there is little to no actually learning of python, just some simple outputs -- really missed the mark in teaching us python to solve these problems.

I was following this specialization since course 1, unfortunately, I only found course 1 easy to understand for someone like me with good background in computer science. However, course 2 and 3 were very hard to grasp. I would suggest to start each topic with a simple visualized example to explain and demonstrate the essence before delving into the math.

In my opinion, I think the course is not as good as the first two courses of the specialization. The explanation of the python libraries from week 3 and 4 are very poor and should be improved. However, the theoretical regression section is well explained and carried out.

The course made things even more complicated. The duration of the video being more than 10 mins is only frustrating and the quiz has noting to do with the concepts. The lectures are boring and rushed. Not to the mark

The labs were the biggest drawback...there were lots of labs and there were lots of Python codes but hardly any videos explaining those codes

Messy, too many half-explained ideas

Week 1&2 are done properly. Theory is well presented and coding is enough.

Week 3&4 - complete disaster, complete garbage. Throughout the entire Statistics Certification (module 1, 2 and first 2 weeks of module 3) the difficulty is increasing at a slow pace and they make sure to present the knowledge at the same pace. For 3 and 4, they do not acknowledge at all that the difficulty of the topic just skyrocketed exponentially and they just do an expositional dump of 4 videos without any real-life example. What's even worse is that they send you on different websites to better understand - which you do - and than when you come back they teach you something completely new, without any connections. I just wasted a lot of time, and just skipped through all videos, and just trial&error the quizzes, skipped all the practice and assignments as they were imposibil to learn or even attempt. Whoever designed weeks 3&4 should pull down immediately from Coursera and let someone else do a better job. I absolutely advise to stay away from this 3rd module (or at least do the first 2 weeks, if you are not interested in the certification)

My final specialization course certificate not received, even after completing all courses in this specialization.

too much material, way too little practical examples in python

Week 3 and 4. Really painful. truly...truly...painful..

bad