Great Great Great Great Course. Just too Good. After this course, I get to know why The University of Michigan is so famous. They give their hard work to build courses and curriculums just great courses. Thankful for their Aid. God Will Bless You Guys. Because you are just working for Humanity First then something else after that. Thank you very much for your Great work The University of Michigan.

This course is perfect for understanding the basics of Data Science in real world scenarios applying python libraries such as pandas and numpy. The course assignments are interesting, but require a lot of investigation and self-learning. The instructor´s explanations are clear, and there are a lot of complementary activities. Python background is needed. Looking forward for the plotting curse. :D

It seems to me self-learning is more important than watching the videos. Every time I used a lot of time in finishing the programming assignments.

Suggestions: give the standard answer of each assignment so that we can improve the coding skill. (yes its difficult in not showing to the ones who has not finished the assignment.But to those who wants to learn it is important. Thanks for the guiding)

One of the best courses i have taken up so far.I am really happy to complete the course gaining a vast knowledge in Data Science at the same time improving my python programming skills. I cannot express how good was the instructor(Christopher Brooks) and also i really thank University of Michigan for providing this course. I would really recommend this to my colleagues and friends . Thank You.

This was an extremely well designed course. Assignments were very challenging and I had so much fun doing them. Solving the assignments give a true sense of accomplishment. Special thanks to instructors and mentors who help students in understanding the assignments. This course could not have been completed without their help. Thanks to University of Michigan for offering this specialization.

Excellent course! It is demanding, as you need enough time to read the complementary material (book by Wes McKinney) and for the assignments. The videos of the instructor typing in the markdown cells as closed caption is not very didactic. Although what he says is absolutely relevant. The assignments are challenging and requires more time than what Coursera suggests (about 3h / assignment).

The course is very well structured from notes to assignments. Lecture content is to the point and lecture length is just right.

A lot of work has been put into the Assignments and Juniper notebooks. This element makes the course invaluable as you learn through practical experience. through well thought out and planned questions.

Thank you for making this quality of education available to all.

I have learned a lot from this course it is maybe the best course or one of the best so far. I come from a French-speaking country I learned English for six months before taking this course . However, what I like the most about this course is the way he is speaking.

I thoroughly recommend this course to everyone who wants to go for a career in Data Science because it is an excellent course.

Excellent course for students with some knowledge of Python, but not for the complete beginner. The assignments revolve around using pandas with real-world data and are the best way to solidify what was learned in the lectures. The exercises can be time-consuming and you'll end up perusing Stackoverflow and the pandas documentation often. It's nevertheless an investment that pays well off.

Excellent course, and very well taught. The projects are a bit difficult for beginners and will require independent learning as well as revising the lectures, but such is anything important in life.

The only thing I think the course can benefit from is a printed summary of lectures, since they can be quite dense with information! But I think the Jupyter Notebooks are a good inclusion as is.

It was a great course and I enjoyed it immensely. You get the most out of the course when you go deeper in depth than what was discussed within the video lectures. Assignments can be tricky, definitely worth attempting, and it is important for you to understand the problem before trying to code. If you are stuck with the assignments, posting your questions on the course forum is helpful!

I overthought some of the homework (the forums will tell you to not do that) and wasted much time going a bit too far cleaning data, however my own hubris aside, it was a good course. I've been working in NNs for some time, but wanted to use more formal data science tools on top of that and add something to my CV. I wish these tools had been around when I was in grad school... le sigh.

This course has been very helpful and has motivated me to pursue more in this field. Most of my concerns and doubts are addressed in the videos, the instructor's explanation is very clear and understandable. The only suggestion I have is, to lay a little more emphasis on the python terms pertaining to data analysis, so that the student will have a better understanding and memorizing.

A great practical course.This course will make you think and search a lot on stackoverflow,which is good because a lot can be learned by doing it ourselves.Then why this course because we need to know what to look for and this course gives us the basics and we will be able to do the assignments by ourselves .Its not really tough but will need some time to get all the answers correct.

Well, this course is quite good. It's obvious that the staff put a lot of effort into the course. They answered students' questions and solved problems which helped a lot. I learned basic programming skills of Python and the usage of library of Pandas. The professor gave the outline of what you need to do and the most of the work is done by yourself. Very happy to take this course!

It is too hard as a second course after 'Python Basics', I have to admit that I search a lot of tutorial to pass the assignment. I suggest more steps by steps examples should be given in the videos and/or readings. That would be much easier to understand and digest. But, overall, I learnt a lot in this course. And I will spent more time to review the content in this course. THANKS.

Great course! The lectures explain topics very well. The assignments were challenging - you might want to do a beginners Python course before enrolling into this course. I liked that assignments were focused on independent learning where you had to go online and look for the answers yourself. I believe this form of learning is the most efficient one. Great course, highly recommend!

A very clear introduction to using Pandas for handling data. The integration of Jupyter Notebooks in both the assignments and the in-lecture pop-ups was very effective. I also appreciated the balance of covering most of the material in lectures, but leaving you to track down some things for the assignments. I can only hope the next courses in this progression are this well done.

I'm an experienced data analytics professional re-skilling after being laid off. I really enjoyed this course. Professor Brooks' lectures were engaging and clear. I found the assignments to be great practice, although they were challenging for my level of programming experience.

I strongly recommend having some skill with python, particularly pandas, prior to taking this course.

Great course to begin with. If you find this course to your liking you can enroll for the whole specialization. The instructor is fundamentally clear and easy to understand. Some of the codes may not make sense as of now, but I am pretty sure it will make more sense later on. I felt a little more content could be added to the videos and this would be even more easier to grasp.

The whole course is quite demanding for me who do not need to use programming at work at all. However, it's challenging and I really feel that I have learnt something. Even the teaching staff are very helpful and the replies in the forum are very useful in completing the assignment.

The final project is a bit difficult but I hope that I could apply it in real life situation.

After studying the course of Andrew on Machine Learning, I want to study a course , which focus on python. I once chose the Machine Learning Specification , but the course use the non open source python packages. And I tried this course. I used about 4 days to finish the 4 weeks, and get myself familiar with pandas though I have no experience on python and pandas programming.

Great overview of Pandas and ETL using Pandas and Python.

Assignments and final project were challenging and realistic in terms of how you might use Pandas and Python in real world situations.

The auto-grading of projects can be annoying with error messages that aren't clear or accurate. If you aren't clear why an answer isn't accepted, then don't hesitate to search the forum.

It's been a phenomenal course. Highly recommended for new comers. Instructor teaching style was marvelous . Professionalism was there. Moreover course demand reasonable analytic and programming skills to do it properly quickly with proper understanding. Learnt alot of new ways of data manupulation which i have not done before. Thank You Coursera Team for making it possible

Excellent course with rich mixture of course material from useful video lectures, quizzes, links to published papers and supporting websites, book references, discussion forum and of course the interactive online assignments. I appreciated the course submission process and the ability to check and re-submit assignments. Cant wait to start the next course in the series.