This is very helpful course, my skills horned after undergoing through this sessions. My expertise and style of using python for data analysis changed. Articles and group discussions about P-hacking made me to realize the pitfalls, I may enter once I get addicted to proving my hypothesis correct. I got an idea, what better I can understand; when data speaks.

I am waiting for next module of this course. Please start it as possible.

Loved almost every bit about the course: the material, the learning pace, the instructor. One thing I would request is to update the python libraries in the assignment. In doing the assignments I came up with solutions which works on current library version but not for their old version. Had to explore old apis to complete those assignment which was kind of stressful especially for setting up the older python libraries locally.

This was a nice course even though I knew most of the stuff before hand lectures still had something new in store for me. However, I found the programming assignments challenging because even though the submission checked our solution if I got it wrong it was extremely difficult to pin down the mistake and the instructions itself couldn't through a light on my short-comings.

So I learned the hard way. It was a great experience.

Overall I thought the level of the course was good. The programming assignments were complex and long enough that you had a good opportunity to re-inforce topics covered in the course. I already had a good bit of pandas experience so the course was helpful to re-inforce things I was already familiar with but hadn't been forced to try out. I think if you don't already have pandas experience the assignments might be tough.

This course helps me a lot in understanding the very basics of Python programming. Although I have been using the language quite a lot, sometimes I do not know that my codes are *far* from efficient, and I know now that it was due to my lack of basics (I hopped around online forums now and then, copying codes from here and there). From this course, I am now more confident in making my own code. Still lot to learn, though!

Immersive and challenging introduction to python/scipy libraries in just one month.

The thing I like the most:

Assignments make you think twice, they are challenging enough to make you investigate further on your own about a probable solution

What I disagree:

Time marked for each activity in course (specially programming assignmenent resolution) is non realistic, actually takes much more than 1..5 hrs to solve the assignment

Challenging course. Worth the time and effort I put in. Instructor and the material is excellent.

One suggested improvement could be the guidance for assignments could be tagged better. It takes a lot of searching before one can find the right material. Both Sophie Greene and Yusuf Ertas provide excellent support. But if the guidance or tips can be made easily disoverable, it would save a lot of time.

Highly recommend.

Very nice introduction to the pandas library, with special focus on practical exercises. It might be a bit difficult if you have little experience with python, but it is not impossible. In my case, I needed more time than expected to finish my assigments because of my lack of experience with the language. Still, the forums are usually very active and the Teaching Staff is very helpful, so I'm glad I took this course.

Really awesome course. It is a kind of do it yourself course.The assignments are tough to crack. I think a little bit of programming experience is neccessary. The lectures themselves only give the basic knowledge. The assignments make you do research on the relevant topics. The autograder is pretty bad, it gives false negatives a lot of times, but that i believe is Coursera's drawback and they are working on it.

This is a really good course if you are a beginner and want to learn Python. Assignments are not easy, but not impossible, and that is the best way to learn. After passing the course now I feel I need to stop and go over everything again to be able to make my code Pandorable, because right now I know it is not, it works, and I understand it, but I know it can be better. Thanks to the team for this great course!

A great course if you really want to build your knowledge and develop skills in respect to using pandas and numpy. The assignments are challenging to an extent and will make you dig deeper to find answers and ways to apply everything you learn during the week. A good example of a course where learning comes mostly from practicing what is taught rather than just watching videos and answering quiz questions.

Nice introduction to pandas. Lectures are short and give just a quick overview of the different sections while the main learning comes from the assignments which require more individual effort and self-learning. Material requires some basic prior knowledge of Python and/or experience in another programming language. Would definitely recommend this course to people interested in data analytics with Python.

Excellent course for data analysis in python, although the assignments are quite challenging and time consuming for beginners. During the course, I wish I could access to the correct codes after passing minimum score so that I could compare what I did with what common practices would be. We all code in different ways to achieve the same outcome, but it would be nice to know the most efficient ways/styles.

One of the best Python/intro to data science courses online. The assignments were sufficiently challenging and realistic, and I certainly learned new skills by completing them. I also appreciated the links to the articles and podcasts that gave me new perspective on my work. Also, a big thanks to Sophie and the other moderators on the discussion board, as the existing discussions were incredibly helpful.

I did not expect that this would be so fruitful in my career.I was just exploring this portion of technology.Now I am kind of emerged in it.Thanks to University Of Michigan and the respected professors for giving me this opportunity and Coursera for giving such a platform.Sometimes it becomes hard to access the resources and knowledge like this ,but coursera made it very easy now to get access of these.

Everything is taught from scratch, which makes this course very accessible- still requires effort, however will leave you with real problems,confidence and understanding of subjects covered.

It was very helpful and easy to learn.The quiz and programming assignments are well designed and very useful. Thank Prof. Christopher Brooks and Coursera and the ones who share their problems and ideas in the forum.

Very informative course. It's a little fast paced but you can always go back and watch the videos again. It teaches the basics of pandas with a focus on how to prepare your data before starting working on it

You certainly need to do your own research (Google, StackOverflow, pandas documentation) to complete the assignments.

The mentors on the forums are the best! Without their help I would have been lost.

I appreciate this specialization's patience to begin teaching data science with such a thorough introduction to handling data in python. The lectures are concise, with 80-90% of my time time spent on the assignments. The creators of the course have a clear understanding that most of a data scientist's job is spent cleaning data, and it's incredibly important to get the practice offered by this course.

One of the most satisfying and challenging online courses I've ever taken. It's a densely-packed, fast-paced course and the assignments can be a bit challenging. For the assignments, we are provided datasets that are similar to the ones that we are likely to encounter in the real world. This course also teaches us to refer the official documentation and where to look for when we encounter problems.

This course was excellent! It is hard to believe this is an introductory course given the difficulty, but this course touched on all of the skills I was looking to improve as an amateur programmer / data scientist. I would highly recommend this to anyone who has a base knowledge in python / pandas, and I very much look forward to the other courses in the specialization. Thanks Christopher and team!!

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.