Overall this course provided content to familiarize oneself with statistical analysis in python. I'm particuliarly thankful for the step by step labs and excercises available on IBM. In some cases, the course materials don't seem to cover content that is included in the evaluations. In those cases, I suggest to reference outside sources. Also the experiences with IBM Cloud have been frustrating. Partially becuase the environment is at times unavailable when needed. In addtion the environment has been undergoing upgrades and changes, and the course materials are not up to date with the changes in the cloud environment. Ultimately though, dealing with unstable computing environments and reasearching outside sources to successfully complete projects are skills possibly more valuable than knowing how to compute statistics with Python.

This was an absolutely useful course to introduce the student in the topics of normal distribution, calculation of probabilities and hypothesis testing applying Python.

Visualization and statistic charts are covered as well.

Examples were given in a meaningful way, nevertheless I would give 5 stars if teachers could focus more on the theory of inferential statistics.

Quick basic statistics with python. Some topics were explained better then others. For example t-test was explained well from statistics point and how to do it in python, meanwhile linear regression was just shown how to do it in python and very quick overview of output data. No background explanation or how to do it by hand.

Assignments in week 7 of the course are completely unbalanced. The main questions are at the beginning , and the source data and the necessary libraries are at the end of course. There is no sequence , which increase in the time spent on the work.

It was a decent course.

It could be more "learning by doing" oriented, there are some concepts like hypothesis testing that could be presented in other way, It'd be helpful if it had some real world examples of that.

I loved learning here; it was explained so well and all the modules here are too fun to learn <3

The course is very very nice. Got great hands-on experience on statistics with this course.

The course is super useful, but I'm not a fan of the peer-reviewed portion for the project.

I highly recommend this course for anyone that is having problems with basic statisitcs.

very interesting course, however, IBM Watson Studio was difficult to use

good content, annoying work with ibm tools

Very nice and easy course

Good introductory course

The assignments are very well prepared but the theoretical part is not clearly explained, I missed the structure, in particular, a more generic intro to every lecture and connection between lectures/slides would make it easier to follow. Also, additional animation to a table or a list of items and using a pointer to make it clear what exactly is explained at the moment would help.

It gives pretty basic information, so there isn't depth into the topics. Also the examples are the most basic ones.

Final Exam question on one/two tailed test is bugged. The options are all incorrect

Need to explain in details the statistical elements and uses

Probably the most convoluted, out of touch, amazingly confusing ways of describing ideas and methodologies used in stats I've ever witnessed. It seriously seemed like they had some of their engineers come without being told what for, and asked questions on the spot to answer. Some of it was to the point I have my friend watch parts of videos because I was laughing so hard.

very basic one , course looks like preface only. seems only want to tell the topic which are there in statatitics. there is no details provided in this course. not usefull at all.

None of the tools work and I'm struggling to pick up the practical skills being taught. I've dropped out of this and would like my money back.

Has very little to do with Python and all about doing statistics manually.