Very low quality of the course. The structure of the course is illogical. Also it takes too little effort to accomplish the course. In the beginning of th course labs contain all the code so a pupil doesn't have to do his/her best to solve tasks. I can just constantly press ctrl+enter and get my certificates. It is not what I expected from the course. Also quizes never contain coding practice, so to accomplish I just need to show the understanding of the basic aspects of the topic, not the coding skills. The, at the end of the course (after I have lost all the motivation during the first weeks you give us difficult function, including custom functions, never explaining them at all). Have a huge doubt about buying the subscribe for the next month.

So many mistakes in videos and labs, including spelling errors, misnaming functions and code that causes errors.

These have been listed extensively in the course discussion forums, with some complaints from over 6 months ago, and have not been addressed

Many typos and other errors. My favorite was the video where they said "150 - 50 = 50"

I am working through the IBM Data Science Certificate courses (in order) and this is easily the best one I have taken so far. Once again, the labs provide a variety of hands-on exercises that help to cement the topics introduced in the lectures (which, to be fair, are very fast-paced). Everything taught is practical and relevant. One request would be to fix the pacing of the videos and lecture quizzes, which often appear to test students' comprehension mere seconds after the topic was discussed! I did also notice a few errors in the labs, but they did not stop me from learning the material. Overall, great course.

perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.

Very serious, professional, empowering course. Clear straightforward detailed explanations. A good deal of practice.

best course for beginners

This needs to go much more in depth on the options for analysis, and provide more examples.

In addition, the labs and final exams were not fully completed/corrected/reviewed, so there were many erroneous issues, including assumptions made that was not clear to us students.

A seriouse deal of statistical modelling taught with a perfect content. I really appricate the effort put in order to not being "hard-to-understand", but still finding the way to teach complex statistics. You will have a very good useful knowledge of statistical modelling without getting lost through too many greek symbols and long explanations.

Thank you so much! - Oana

None

Does an excellent job in providing the Python commands needed to do data analysis, along with some descriptions of what the steps actually involve. Has quite a few typos and minor issues -- looks a little sloppy.

I felt the course isn't designed well as it takes you little fast than expected and doesn't explain all the terms! May be one has to be very good at math or revise all the topics before taking this course.

I have really learned many things in this course which are meaningful and helpful in real life. It is not just lines and numbers , it is exciting how you can apply these methods to find solutions in your real life problems. Combined with strong Python skills , you will enjoy more..Thank you

This was a great review of stuff math I learned in high school and college. Of course it's all easy now because it's baked into Python. We used to do it by hand and with slide rules back in the early 1970s

It is really a good course, simple to understand and very complete. Thank you !

Recommended course to understand the how to do data analysis using python

Well organized, good explanations, and very good labs.

Overall apt content for beginners and naive learners.

Great experience

The techniques, methodologies, and tools presented here are essential parts of the data analysts tool box. The coverage was, in general, well done. I am glad I took this class, and look forward to the next.

That said, there were problems:

1) The meta parameter, Alfa (or is is Alpha) is never explained, except that it helps. To be useful, the student needs to know a bit more. Also, the spelling should be consistent between the training texts and the lab.

2) The lab needs maintenance to keep up with changes in the Python packages. I received warnings about using deprecated functions and values.

3) The text needs grammar/spelling checking, for example, the end of the course exam is labeled "Quizz"

Instead of having a lab after each topic, this course one lab per week encompassing all of the topics. Some might find that better than having smaller labs but to me the information was assimilated better when i did a lab right after the topic. That being said, you can open the lab first and follow along with/after each video. You just need to be mindful of what works best for you. Taking time to understand the code is a must and some more documentation would be helpful. I wasn't a beginner with Python and it took some time and work out what was happening at times.

Decent introduction to basic concepts of data analysis. However, the 'labs' and quizzes feel insufficient to practice the theoretical aspects. Further on the downside, the quality of the material in this course is quite poor. Even worse, several months after learners mention errors in the discussion forums (and partly get an instructor response), the mistakes remain in the material.

The course had plenty of errors in the videos, Labs and quizzes. The explanations were rushed at times and quite a bit was not easy to follow. The worst course so far!

Really intensive module. Be prepared to learn a lot here. You'll be diving into real stuffs that wil ask you to listen carefully and understand the matter. My advise is to take note of any points that you are not comfortable with and make additional research on google/youtube to become friendly with it.

One of the top module i've complete so far on Coursera. Full of usefull, meaningfull information and knowledge.