Although this course covers the very basics (and does not really teach you about how things work), you can learn the most with the assignments, since it is very likely you will need to go through the docs/ forums to get it done. Very good intro to regex and pandas.

Good course. But the Assignment is very tough. It requires almost everything which is not covered in course. So its like reading on internet than this course. I would be happy if this course will cover the topics on which the assignmens has question. So we read it

Although I had some background with Python and Pandas, this course brought new insights in both. With practical examples, it reinforces the conceptual understanding about working with data. I highly recommend this course even if you are already familiar with Pandas

Hace falta abordar mas temas en las conferencias o mas ejemplos, es bueno buscar y explorar por uno mismo las capacidades de les herramientas pero en cada assigment es supremamente complicado, mas aun cuando la respuesta debe ser exactamente igual (sin redondear).

It'd be easier to master the course with a trifle more instructions from the lecturers as to what constitutes a particular function, and what do its parameters refer to. Primarily, I did struggle with having to browse the Internet in search for these explications.

It is the most difficult course I have ever taken at Coursera, but it is also the best course I have completed. It's a different level of Python than the one I learn at my university. The only thing that is neccesary to improve is the video examples of the topic.

While I learned a lot, it was mostly self taught. The projects were appropriate but the notebooks and videos were only marginally useful in completing the projects. I consider the course more of a directed study than a traditional classroom learning experience.

A good course for the data preprocessing and getting used to the NumPy and Pandas library in python. An overview in provided in the contents and video lectures but the refrence books are very much helpful to understand the course.Also assignments are very good.

The topics are useful and the videos are good, my one gripe is that in my experience the assignments take much longer to complete than the suggested time. I was completing the training alongside my fulltime job and had to push back my deadlines several times.

I thought this course was very interesting. The assignments were a little more difficult to complete than I expected. I think a few more smaller assignments that highlighted the skills necessary to complete the final week's assignment would have been helpful.

Excellent material to get you quickly started in data-science with python. The course coverage is less, covers just a few topics. The assignment problems, at the end of each week, are of high quality, but the issue detection can be sometimes be daunting task.

Assignments are very good....the background of video's is distracting and explanation of examples just by talk and without proper slides is not so good.

Please adjust the time it takes to finish the assignments to at least twice the posted approximate time.

The materials are very limited here, most the learning is done from outside materials. While on one side it is good because we have to actively researching, it will be better if they provide a bit more of materials here. But the assignments are really good.

Very helpful for learning data science, but the videos go way too fast and don't cover nearly enough material to do the assignments. The assignments do force you to learn how to python, but through lots of googling, stack overflow and pandas documentation.

They follow a practical approach and present you only the very relevant material so you do not stuck too much into theory. Note that this is an intermediate-level course and you need some experience, self-learning skills, and some patience to be successful.

This course will help us to get more knowledge on python & machine learning concepts thouroughly.

Also this cousera certificate gives benfits to us for semester usage and job point of view.

happy to learn so much of new concepts in online at our home

Thanks!!

The exercises and content was very good but instructions/explanations were not very detailed with most of the concepts left for self study. But overall a great course in terms of getting you started with pandas for effective data analytics on tabular data.

The content and the instruction were great: just the right level for someone like me with experience in other programming languages a decent familiarity with stats.

There were a few glitches with the auto-grader for the assignments, but nothing to onerous.

A great intro to pandas. Challenging even for those with experience using the library. There were some struggles with the autogravder, but they were being worked out, and the integration of the Jupyter notebook system directly into the class is fantastic.

While the course was great, the Jupyter notebooks and the background shells gave me several unnecessary errors. While this was a smaller issue, I think the practice Notebooks should be somewhat in line with the assignments. I struggles on Assignment #3.

The course was a unnecessarily hard because of the lack of feedback from the grader, unclear requirements / function definition in the final project and difference in the file downloaded for the project and the one used in the Coursera python notebook.

Good materials and videos, iteresting exercises - the only thing I would improve is the exercises description - not for all of the exerisises it was clear enough for me (especially as I'm not from the US and I'm not familiar with your census data :) )

I learned a lot through the challenging assignments, but the course materials (videos) are not very useful. They only cover the very basics for the assignments, so be prepared to study a lot on your own. Knowing pandas beforehand helps a lot too IMO.

This is an exceptional undertaking by the university of Michigian for benefit of the students in the field of data science and Machine Learning.This is perhaps the only course which focuses on real world application of data science skills to practice

Good explanations, well structured. However, I wish the weekly content would have prepared better for the assignments. If I have to add another 3h per week to find the right advice on stack overflow, that must be stated somewhere so I can plan ahead.