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Course is good, but in this short course it is covering lot of thing thatswhy lot of topics are just touched intead of going little bit deep into it.

You learn a lot, good intro to data science with python. Labs have typos and can be confusing at times though, the only thing that could be improved.

A very interesting and easy course. Anyone can catch up with big concepts with little effort. Thank you 糖心vlog官网观看 and IBM for this wonderful course.

Course is nicely designed and pare explained well.

I would have liked to see the steps along with the final answer to the peer assignment questions.

Very good course. I wish there were more hands on exercises. We only had a chance to practice in one lab per module; otherwise, I learned a lot.

tbh i was kinda of nervous regarding how will i complete the course without any prior knowledge about any libraires..this course helped me alott

Great course to start learning python applied to analysis, but after this, I prefer to use R. Less complicated and can obtain the same results.

The course material is good. However, I found the videos a bit fast and the automated audio speech is not so good. The lab sessions are great.

I find this course useful. But some of the contents are little advanced all of a sudden and feels some important explanations are not covered.

Through out the course i have learned alot like data visualisation mainly.I think i have completed successfully basics for machine learning.

I feel like this section needs some more hands on labs. Great topic over view and application. Not to much in the way of math unfortunately.

Very informative course, overall it is very well-done, however, there are some issues regarding a few depreciated attributes or parameters.

Exercises could be more difficutl, however I really appreciate the content and the way the course is given. Congratulations to the authors.

Good course for beginners. Can introduce little more concepts such as multi-collinearity, model accuracy etc to make it even more complete.

A great explanation of the concepts and methodology in data analysis , i wish we couldve gotten more peer reviews like the last excercise

It was a good course overall. Would prefer explanations at a slower pace and more examples for each of the techniques explained.

Thank you!

Content : 5/5

Labs : 5/5

Final Assignment : 3/5 (It was quite easy to complete as there we instructions and code already written for you).

need better practise questions preferably to write program instead of multiple choice answers plus needed more theory of the topics given

Very good course, i belive its recommended to explore and read documentation of the different python libraries for better understanding.

Great material. Very comprehensive. The only knock is sometimes the slides, notebooks, and quizes have typos or are not super-organized.

Una visi贸n muy amplia con acercamiento a una amplia variedad de herramientas. Faltan m谩s ejemplos de uso, ejercicios y casos pr谩cticos.

The learning are too basic, trust me in real world things are much critical. Probably coursera can help us with that kind of knowledge

One the greatest course of Data Analysis. The info given about statistics is very important and accurate.

Thank you to the instructors.

The more advanced portions of the course felt a bit rushed without enough examples and hands-on work to really reinforce the concepts.