The course was really good and forced me to intensively check on my weak points which I really much appreciated. The only "weak" point of the course is the automated graduation, but it's just a question about getting accustom to it to better organize ones strategy to pass the certificated. Well done, good job Coursera and University of Michigan. It was really fun, I like it and will continue !!!

The course is a good introduction or overview of the use of Pandas, it's pretty concise so you def need a lot of self-learning beyond the short videos to be proficient with Pandas or complete the assignments easily. I spent more time than expected on the assignments because I'm totally new to Pandas. But the materials are overall pretty good and useful, giving you a guidance of learning Pandas.

This course was very helpful as it gives great experience working with real world data, rather than clean and prepared datasets. However, I can imagine this course would be challenging for someone without a lot of experience. I think the course could also have been a lot better if there was a way to see what about out assignments were wrong or see the actual answer when the question was wrong.

Week 4 lectures could have focused slightly more on hypothesis testing, perhaps delving a bit deeper into the thought process and methodology of coming up with hypotheses, designing an experiment to prove it, executing it, summarising and interpreting the results, etc. Since this is major part of programming assignment in week 4, this could have made the lectures more interesting and relevant.

The course content was great. But I felt the course duration was very small as I was able to finish the course in two days. Prof. Brooks explained each and every concept in a very easy, understandable and lucid manner. In my opinion, this is a very beginner friendly course but the assignments will definitely be a bit challenging for people are intermediate and advanced in python programming.

The assignments were far difficult from what was taught in the course. Significant amount of searching the web had to be done for finding syntax. It will be helpful if a helping hand is given in the form of most probable syntax that can be used in the form of pdf along with assignments. The syntax in the assignment were far more sophisticated than those taught as part of the video. Thanks.

Very good class - but it does require quite a bit of outside study - reading up on stackoverflow. But after this class, the student will be able to have a very hand set of tools/skills to tackle datascience projects. BTW, python with the interactive notebook is very popular in actual datascience projects in the commercial sphere, so this class can be leveraged directly in the real world

This course was much harder than anticipated given it was also my first introduction to Python. Knowing Python coming into this course will make it a lot more manageable. Overall it's an excellent course which touches upon a LOT of items. Given more time on each item, this course could span 10 weeks easily. I now have an understanding of Python basics along with Pandas and a dash of numpy.

The course was great. It provided the learners to search for various concepts on their own which really added the knowledge gained through videos. I feel that best method to approach a solution should be provided after completing each assignment because there was time when I used long approach to get answer whereas it could have been done in a short way too. Overall, the course was nice.

This course is definitely not for beginners. I have a lot of experience working with data in other programming languages and found the assignments very challenging. Lectures are very short and do not really teach you the material - you mostly learn from doing the assignments, which are well thought out and mimic the types of projects that would be done in a professional/academic setting.

In the end I got what I needed from the course but it was more through assignments than the video lectures which go through concepts very quickly. The assignments are good / challenging and require you to spend good amount of time on google and stack overflow but you end up learning a decent amount solving them. The auto grader can be frustrating at times but the discussion forums help

Excellent Course for beginners to start learning pandas and get a pretty good hands on experience in it. The course's assignments are really competitive for me who knew little python (not pandas) before undertaking this course. There is a slight sudden change of concept in week 4 that requires a lot of self learning if (like me) you have little knowledge of data analytics or statistics.

This is an amazing course, I got to work on the real life problems which was complex indeed. Completing every assignment was not easy, passed them after several attempts. I would say one downside is that I had to spend a lot of time googling and on stack overflow. just to give a feel, an assignment tagged 4 hrs takes nearly 20 hrs to complete. Its a great course, be ready to sweat out !

This is a good course if you have had some experience with the Pandas module in Python prior to taking the course. Pandas is a very powerful module but it has a fairly significant learning curve. There are all sorts of free Pandas tutorials available on the web. I highly recommend familiarizing yourself with the basics of Pandas prior to taking this course or you will probably struggle.

The course is designed in a good manner. I would prefer slightly more material in the videos. The exercises are good, they definitely took more time than assigned. A few times question in the assignment is not very clear (that need a bit of work). I definitely learn many new techniques by listening to the videos, changing the class room notebook and last but not the least assignment.

Nice introduction to using Python, but lecture vignettes moved a bit too quickly. Assignments required far more than what was presented in lecture. If not for a particularly heroic mentor, assignments might not have been doable for some like me. On the whole, though, I am grateful for the course and that, at the time I took it, all materials and assignments were available to auditors.

The course contents are well structured but the video lectures are not enough to master the assignments. More detailed explanations could have been included, since its really difficult for a person who is new to PANDAS. The assignments were challenging. Feed back for the assignments submitted were not found so useful. Although, the course contents provide enough space for learning.

For me, this was a difficult course in which I learned a lot. I did not find the materials (videos etc.) provided in the course so helpful, but the assignments you get for your own programming are very close to real world problems and will give you real experience. So you will need some other material to learn, I recommend the book "Python Data Science Handbook" by Jake VanderPlas.

Unlike other courses the lectures are packed with new concepts so much that you can't miss even a minute to understand it. The assignments are fairly challenging. The only part frustrating was working with the grader. Often it won't work and you are left wondering what went wrong without a great explanation. Overall great first course in the series. Looking forward to the next one.

It was a challenging course as a lot of things in the assignments you have to learn yourself. But it was the right way to do as during the work often times one will get stuck on something without any step-by-step directions on how to solve certain issues. The only thing I didn't like about the course is a bit unclear questions in the assignments which took some time to figure out.

Overall, I liked the course but there were some flaws (not too big ones but still worth mentioning) - The way things were explained seemed more like just giving information about something rather than explaining it well (of course at times!). Exercises were really very good as they promoted individual learning more than just depending on what was taught. Recommended for beginners/

This course was tough but I learnt a lot. I really wish that they posted the answers for how the lecturers would approach the questions (even if it was only after you passed the quiz. I walk away from these quizzes not always sure if I made a bad plan that works or if my solutions is good/elegant. This would be very useful especially for us who are early in our coding careers.

I really enjoyed this course, but i am so glad I came prepared and had completed other Data Science tracks on other online sites (Codecademy, Dataquest, DataCamp, etc). I had to put all the skills learned elsewhere to good use in this course. The course was challenging--which is why I wanted to take it! I feel like I had to problem-solve, code, and work with data at a high level.

The material is great, but a tad quick-paced. A little more detail into some sections could be helpful. My biggest grievance with it is that the notebooks and autograder use an extremely outdated version of Pandas and NumPy, which leads to a lot of the official documentation being unhelpful. You can fix the problem within the notebooks but the issue persists with the autograder.

Great professor to listen to and pretty good videos but some assignment questions super challenging and very different from the examples. First three quizzes were weird as they were mostly simple but took 24 hours to output grade. Other than these two complaints, good course to understand how data manipulation works and to learn more about Python's data specific libraries.