This was a great course to learn Pandas and to feel capable of manipulating data in a Pandas Dataframe. The class was laid out very well with quality instruction and good examples in the jupyter notebook. The homeworks are where I learned the most as I really had to understand the material to complete them. I'm looking forward to the next class in the certificate.

Requires a tremendous amount of self-study and trial and error if you're starting from ground zero in terms of pandas knowledge, but the reward is a level of comfort and facility with pandas dataframe manipulation. Definitely a learning by doing experience. Cleaning datasets and manipulating dataframes turns out to be pretty fun once you start getting the hang of it.

The course is challenging for a newcomer to Python. The instructors rely on the student's self-learning to fill in the gaps needed to solve the course assignments. It's been a great way, albeit a little stressful, way to learn. The course also does an excellent job of keeping the student grounded as to implement a high ethical standard when practicing data science.

This assignments of this course is most useful to solidify your knowledge, and ability to self-study. When in doubt, use Forum, as many students past and present have all shared your frustration and most of all everyone's learning experience, which make this course a great one! Thanks to all instructors, teaching staffs, and fellow students, you guys are wonderful!

It's a nice course for Beginners in Python Programming and who have interest in Data Science. It requires a little dedication and lots of programming. The Discussion Forum is amazing it has everything and special thanks to the Mentors Sophie and Yusuf during the assignments. It requires lots of self-learning and a little research for every programming assignment.

Python is huge. Course helps you focus and apply Python to data science.

Me? was new to Python; was novice at programming; had strong background in math and business (both helpful, but not prerequisite); read "Python for Data Analysis" by Wes Mckinney to supplement lack of programming experience -- focused on numpy and pandas chapters; frequented stack overflow

The gains from completing the assignment itself are very large, although this process is very challenging for me who are not familiar with the Python language. Thanks for the help of the teaching assistant. It is recommended that everyone participate in the discussion while studying the course and learn the contents of the discussion. It will be very rewarding.

Excellent introductory course for data analysis in Python, specifically using Pandas library.

I learnt a lot in a short time. Assignments are not easy to solve, they make you think hard, explore more on internet and on user forums, thus making you grasp the topics in depth. This is the best starter course for anyone seeking a career in Data Science using Python.

Although I have been studying and performing data analysis as a beginner this course totally worth the time and effort put on it. Learning to clean code and use Python properly to perform efficient data analysis was quite satisfactory for me. A side dish that I loved was the relevant questions brought for the student to reflect on about ethics in Data Science.

Excellent for anybody who has to manage large amounts of data on a daily basis. I'll admit that the first week I thought, "Whatever, I can do all of this in Excel." Once I got the hang of it, I realized the potential of this material is unmatched, and I started using Python/pandas/NumPy at our machine learning lab to help us with data acquisition and sorting.

this course is ultimate and it really gives us knowledge and confidence because after passing this course I have completed another course related pandas, and that was very easy going for me.thanks to Coursera and Christopher brooks,I always prefer the University of Michigan courses because their teacher teaches in such a way that u will feel more confident

This course helped me going deeper in the python language, especially for datascience. I learned a lot on two wonderful python librairies : numpy and pandas. The assignments were more complicated than expected but with the help of staff members and classmates I did it. A special thank to Sophie Greene whose intensive comments on the forum were very helpful.

Great intro to data science and some of Python libraries for it.

The exercises can be quite difficult, especially if you expect to have all the answers given to you during the lessons. In order to solve some of them you have to search the web to find the commands you need, which I think is a good thing because it teaches an approach useful in real scenarios.

a little more help from the video lectures is expected. The assignments required a lot of self study which is great but at the beginning, every assignment looks daunting and discourages a little. Although the forums helped a lot in getting through this course, but the majority of the roadmap to take, and all other lessons should be included in the videos.

Great course!! I've enjoyed the assignments very much - from my part it required a a lot of individual investigation / reading through posts to find possible solutions but that's only fair since this is an intermediate course. It was a fantastic experience as the assignments felt like real projects. Thanks for everyone making this course possible! Daniel

Very comprehensive in terms of the amount of material covered and the content covered in the material. Covers a lot of model building algorithms in addition to machine learning fundamentals. Has an intuition lecture in addition to the fundamentals which helps a lot! A possible change could be to use R to demonstrate the concepts instead of Matlab/Octave.

The course was very difficult at the start even though I have completed the course on 'Programming for everybody'. I felt that the content was a bit rushed and was not entirely related to the problem sets. But, I learned the most by searching for solutions on Stackoverflow. It is a difficult course to teach, and I felt that the problem sets were great.

This course has proven to be really helpful to me. I was able to learn additional techniques and ways to use the same libraries. It helped in building core concepts and relate the statistics part to the analysis in python. The complexity level of assignments is pretty good, they challenge you and require a overall knowledge. I will highly recommend it.

The course explores different ways to clear data using pandas. The assignments are challenging, since it is impossible to get to the solutions without going through lots of stackoverflow questions. The course also raises questions regarding the future of data and the problems behind the extensive use of pvalues, the p-hacking problem. Very interesting!

This course requires a lot of extra research using the Pandas' documentation and Stack Overflow in order to past the tests, which are very well designed to gained the most important skills. At first I felt this course was very demanding but as I moved forward to the second and third course of the specialization, I realized how much I learned from it.

This course wasn't quite the cakewalk I was expecting it to be, which is perfectly fine! I definitely would recommend this course for anyone looking to pursue data science/machine learning professionally. I learned a lot of skills that employers look for, and have applied the things I've learned here in other course work as well. 5/5 would recommend.

This is the best course and will make sure you learn pandas, the quintessential tool for data analysis in python. The professor teaches almost nothing, lectures are very thin. He picks you and drops in you in the ocean, now either you will learn how to swim or you will quit the course. Not an easy course, and requires a lot of work from the learner.

Please give us clearer instructions and definition of terms for each project. I don't want to waste time on understanding questions. Besides, it will be great if you can give us more hints on which functions to use, for each question. Because from my experience I find that reading hight quality codes is the best way to learn a language! Thank you.

For the non-programmer, this will take quite a bit longer than you would expect. Very detailed though and the forums provide a lot of help, fortunately since enough people are taking this course to make community feedback useful. A few of the instructors are helpful in discussion forums as well, although sadly not all of them are equally helpful.

Even though it was harder than what I expected for an introduction course (actually it says this course requires some previous knowledge and it is an intermediate level course, i just didn't see it), i really liked it. Assignments were very good and they made me learn a lot of things. However, course lecture could be a little bit more explanatory.