IN GENERAL TERMS I LIKE IT ALL, WITH THE EXCEPT THAT I COULD NOT FINISH THE SPECIALIZED PROGRAM BECAUSE I DID NOT UNDERSTAND THE QUESTIONS OF COURSE NUMBER 5, THE TEACHER ASKS THINGS THAT HE DOESN'T EXPLAIN, AND WHAT IT EXPLAINES DOES NOT DO IT WITH CLARITY !!!

I AM NOT AN EXPERT IN PYTHON, BUT LITTLE BY LITTLE I WAS LEARNING SOMETHING NEW, BUT COURSE NUMBER 5 SEEMED IMPOSSIBLE.

I AM AN EXPERT IN ANALYZING SPORTS STATISTICS, AND I TAKEN THE SPECIALIZED PROGRAM BECAUSE I WANTED TO LEARN NEW THINGS THAT WILL HELP ME IN MY JOB; AND IN COURSE 4 I LEARNED MANY NEW AND VERY INTERESTING THINGS; BUT I COULDN'T FINISH THE SPECIALIZATION BECAUSE COURSE NUMBER 5 IS ANTI-PEDAGOGICAL

IF YOU ARE NOT AN EXPERT IN PYTHON I DO NOT RECOMMEND THIS COURSE !!!

Excellent introductory course on wearables. Makes us think and apply the knowledge gained from the lectures into practical use. Lecturer was good and I was able understand him clearly. This course needs Python and Pandas skills to be at intermediate level. The reading materials provided were also useful. A small problem I faced was with Week 5 lab -- notebooks which explained the concepts in the lab sessions in the previous weeks, was without any explanation for the last week. I'm still not sure why Z-Score metric was used as performance metric. Hopefully they add more context and explanation for future candidates. Despite the small annoyance, I highly recommend the course. Apply for the financial aid you need it and get certified!

This is an interesting course with some great real life insights on wearables and messy data from a lecturer who is both clear and very pleasant to listen to. I am giving it 3 stars only because some of the lecture notebooks and assignment pieces, which should be really central to the specialization, suffer from the same type and level of neglect and abandonment as the first 3 courses in the specialization, which is really sad, as it is evident that all the required resources and expertise is given to deliver a neat, tidy, transparent, and coherent course with genuine, meaningful follow-up. But it seems something else was missing. Time, motivation, incentives, we will probably never know, but the sense of "incompleteness" lingers over this course just as much as the previous 3 in the specialization. Also, in this course in particular, sometimes there only seems to be a very vague connection between the lectures and the notebooks and assignments. The lecture notebooks and the assignments sometimes appear as if they had been just tagged to the lecture videos to make them fit in the specialization, as opposed to follow organically from the lecture videos. The addition of scientific papers and other references is great, though. All in all, an enjoyable and interesting offering, but with some very stern caveats.

Love this course, love the content, love the assignments and Peter is great at explaining the terms and concepts

Suitable course materials, good quizzes and perfect teaching style by professor Peter Brodary

thanks

good !

Very interesting. I found the articles and exercises very useful. I would have appreciated some machine learning algorithms