Great course! If you want to learn more about NumPy and Pandas, this is the course that introduces those libraries. Be patient with the assignments. Even though you think you have the correct code, the autograder sometimes disagree. Dealing with this problem, there is a lot of help to get in the discussion forums. Great instructors as well.

Challenging course with little hand-holding and some independent learning is expected. Marking for assignments was needlessly stringent (e.g. numpy float vs python float) and expectations of answers was not very clearly outlined. Had to trawl through the forums. Nonetheless, very good exposure to pandas for someone just getting into python.

The lecture content is rather short and you have to search a lot on your own. I like the assignments at the end of each week, completing them helped me to understand what I am learning. Good introduction to frameworks, pandas and in general analyzing data in Python. It's quite a lot of work but when you finish, you can be really satisfied.

Some of the assignment questions are difficult understand without the help of course coordinator. I appreciate the help from course coordinators in guiding to understand the question. It was my first course in the series of Python and I could follow everything it was tought. But I am not happy with the short time assigned for the course.

The course is a must-do for a person new to Python, however it ramps up very quickly. I had done another python course before doing this, which helped me do this one. The assignments were challenging in my perspective; however cracking the exercises gives one lot of confidence. Forum discussions helped me a lot to complete the assignments

This is a very impressive course for someone who wants to get an intro to data operation in Python. The assignments are very well laid out. The automatic grader gives good insights of what may have gone wrong.

One thing though- there could have been more concentration (especially in the assignments) on grouping and slicing the datasets.

Spent more time figuring out what was being asked in the assignment rather than solving the assignment. Typos in assignment questions led to wasted hours without understanding why the grader kept rejecting solutions. Course content was useful and I would recommend if you are willing to live through the pain of the assignment submission.

I'm very new to python and the course has been pretty helpful. The format of having the notebook to walk through the course is also helpful. The course's assignments are pretty good too - but could be improved. Some of the instructions are vague/conflicting and I had to spend a lot of time figuring out / confirming the question intent.

First, I would like to say thank you. I learned a lot about pandas/numpy via practising in the assignments.

The assignment content is very good. But the guide and program checker are so poor (as other students mentioned in their reviews). I wouldn't pass the the assignment if I didn't read a lot of tricks/explanations from the forum.

Solid course. Still very challenging without more pointers on basic syntax. There are a few inconsistencies in python that makes debugging challenging - and I don't know what to do about that. Otherwise, the course achieved the goals.

One thing that would help would be more testing on basic knowledge of how to access panda dataframes

frankly, it takes a lot of searching information on one's own, outside of this course.

I raked my brains for the most of Saturday and Sunday and finished two last assigments although I still don't feel strong in pandas, neither there is much material left here for me to come back and review something step by step in a systematic way.

Got to learn new concepts of pandas and numpy libraries. The course is very informative, and provides a good amount of basic knowledge, through which one can proceed in the field of data science. Things I didn't understand well, were the ttest_ind library and the matplot library. The lectures should be improved on these concepts.

Videos could include more information. Instructions in assignment 4 were not sufficient. Had a lot of difficulties in assignment 4 as I could not understand the requirements in question correctly. Questions could have been more detailed and stepwise.

Links to some datafiles have problems. Could not easily download some datasets.

Great course for a Python beginner or someone who just wants a refresher! The video lectures were pointed but not too in depth, allowing the learner to explore a bit within the assignments to get even more information from the interwebs, which is what just about every programmer does anyway when they forget syntax or something.

Interesting course, learn new approaches in using Pandas libraries. One remark, the evaluation of the assignments takes too long, for the last assignment all the answer took 2 minutes to run on my personal laptop while it took 15 minutes when submitting it. I spent a lot of time just waiting for the assignment to be evaluated.

Very interesting subject and data science skills are definitely currently in demand. The only thing that bugged me was that the grader didn't give much feedback on anything you did wrong. On the flip side the mentors did a GREAT job (kudos to you guys). The discussion forums were vital and they were really well moderated.

content is good, and exercise is very relevant for learning. only problem is the exercise is very hard and cannot be finished only with content covered in the lecture, you need to do extensive self learning and take a lot of time outside the classroom. for those without python experience before it is a steep learning curve.

Update your Pandas library and the explanations for all projects. It is very frustrating because you have to deal with both: 1) lack of clarity in the text and 2) missing features for the library we are using. Don't get me wrong... I learned a lot, but it kinda feels not enough when compared to the unnecessary frustration.

I found the material of the class very useful for someone that has no experience using Python in data science topics. However, I feel some topics are given too fast. I also found some issues with the autograder that do not have any implication with the goals of the class but that are important in order to get the grade.

The class is interesting, but I don't feel like the lectures were good preparation for the assignments. I understand that it takes some reading or study beyond the lectures, but there weren't any other materials provided. The Pandas documentation is big and it's not helpful to just go read through all of the docs blindly.

course is very good to learn the python basic pandas, numpy libraries.

I would prefer to have a reference book associated to the course so we reference to it, it will be great for future while coming back and read what we learned.

The grading system consumed most of my time to make sure to have my answer graded correctly.

It's a great course and during the process I learned a lot about python pandas applied to data processing. The only downside I see is that the lectures does not prepare you well enough for the homework at the end of each week. I had to spend tons of time googling about pandas in order to finish the homework each week.

The auto-grader is sometimes frustrating. I know the course staff is providing the code to let learners to find the errors, but it's in the forum and I only know it after several rounds of frustrations.

Please mark those checking codes in the question too! It helps provide a happy learning experience to every learner!

Course is well structured. Most of the concepts are given quite quickly in the video lessons which is good since each learn is free to decide whether she/he wants to do further research in a specific content. Assignments are quite difficult and consume more time then estimated, but you actually get to learn the thing.

this is my first course in Cousera, and i am a novice in Python. I think this course is really impressive. I learned how to use Python to process data quickly. I really recommend this course if you are interested in Python and Data Science. I decide to learn the machine learning course next, I love doc.Christopher!