I very much enjoyed this Data Science course!

However, I feel like there needs to be a more interactive environment between the platform and the student. I saw the mini quizzes in the videos a step in the right direction.

Also, I feel like if there were more videos, uses of functions, and providing multiple cases of real data science problems would be excellent.

Thank you for all who helped in making this course!

The auto grader could use some work, and it should be a bit more clear to users that this isnt't a magic bullet into data science. It requires alot of work and preferably quite a bit of experience with python.

But as a intermediate course with intro to data science I think its great and really reccomend it to people who have dabbled with data science before but never had a good roadmap to actually learning it.

Overall, the course is really good for those new to python and its data science ecosystem and as always the instructor is expert at what he is teaching. In addition to that, the references provided in the course contains much more information for the interested students. The only missing piece for me is course coverage, I hoped to get more details about pandas and regular expressions from the course itself.

Overall, I was very pleased with this class and how much I learned from and practiced within it. I have some adjustments I would make, mostly to the assignment instructions and time estimates. The assignment themselves are well-designed and useful, they just have extremely clumsy communication attached. I would recommend it, particularly since all my complaints are easily fixed. I took it in Spring of 2021.

Positives: I really enjoyed the course and the exercises were a bit tough but helped me learn a LOT of useful information. It is a good course. I will highly recommend this.

Negatives: Some sections are rushed and is not much help. And the software version used in the course is outdated and hence we had to change the code multiple times as the syntaxes are not accepted in the auto grader. This is a shame.

Although is a very nice course, it would be nice to start on easier programming basics. There are specific things that one's gotta' be inspired to be able to think on. Maybe adding a week before week 1, to introduce on certain syntax and intuition so we can put on practice what we learnt on the kernels since the content of week 1.

It was so delightful and challenging, that I want even more. Thank you.

The rating 4/5 is for the assignments complexity . It requires the learner to work through the logic in pandas and self learn through the errors . This is the new way to learn w/o any spoon feeding . I reduced the rating to 4 and not 5 , beacuse I feel more content could have been given taught by the professors or leave a good piece of advice to the learners. 5/5 for Forum support by teaching staff.

For someone knows basic python only some of the things are explained really fast. However, you can catch up during the assignments. A lot of time for the assignments spend on finding possible solution on the forums. From one point of view it is good - so you can find you own style. Form another, if you work full time and have busy schedule - it will take much longer to finish all the assignments.

The course projects rely on material not yet presented and the automated grading system is very sensitive. I struggled with the assignments because when I had a problem it was difficult to pinpoint the source. Some of the blame is on myself for not using the discussion forums sooner, but this is not my first coursera specialization in data science / programming and I can honestly say I struggled.

course material good, mentors very very helpful and active , as mentioned in one of the posts the expected output of an answer in pictorial form can help students a lot , and the assignments were a little on the tough side , even being from a programming background i had to put a lot of effort to figure out silly mistakes and complete this first course but a nice experience , keep it up coursera.

The course is good and provide great challenges to do a lot of things with Python and Pandas. However, I find that its resource material sometimes lacking complex examples. This may be intentional in order for the students to learn from external resources as well. However, this can also causes difficulties for people who are not already familiar with Pandas before they start following the course.

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.