IBM의 Statistics for Data Science with Python 학습자 리뷰 및 피드백

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Good course, many subjects are covered. But be careful if you're totally new to statistics and hypothesis testing, this course is rather fit as a refresher.

Unfortunately the lecture slides are not available for download and some of the transcripts need serious amendments. In all Jupyter labs the kernel did not connect for a long time and attempts to export notebooks as pdf threw internal server errors. Such things are disturbing and could be prevented with proper monitoring and proper technical setup. The peer review in week 6 must be performed without having the approved solutions; this is not very professional.

Overall, the course gave me a brief but informative look at the basics of statistics with Python. Once again, the many practical exercises were very nice. However, the speed of the p-value and regression was a bit too ambitious for me. Would have appreciated some more details there or a good link to somewhat short and informative. But as said, overall, another very informative course.

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.

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

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 introductory course

The course felt disjointed at times and there was a lack of clear explanations. The expectations for the final project (formatting, etc.) could have been stated more clearly to reflect the marking rubric. The final project was otherwise nice and quite summative.

Not the greatest course on this platform. The structure of the course is somehow confusing and it's got a bit old, should be updated and offer better knowledge.

Many of the concepts mentioned in the lectures or the quizzes are never clearly defined. Quizzes test concepts never mentioned in class, and one question contradicts what was taught in class.

A​ll IBM courses need to be removed from Coursera until they can fix them, and Coursera gets a promise that the INSTRUCTORS actually involve themselves in the forums. Anybody who paid for these courses should be refunded their money due to the extreme poor quality. I thought this IBM course would be different than the others, but they went right back into the speed through and not explaining the more complex topics again. The final project asks us to add titles to our statistical graphs, but this was never taught in either the videos or labs. The evaulation metrics are also mismatched with what the actual assignment states. This is 100% unacceptable.

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.

There are mistakes in examples, in assignments, and final project! Creators never respond in Help section.

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