This is one of the best courses that I have come across for Data Pre-processing and the pedagogy used completely mimics that of the University of Michigan where the onus of learning is on students and the faculties just act as a guiding hand.

Wow this was one challenging course! I am someone who started his data science journey a couple months ago, from scratch, and some of the questions on the assignments in this course will definitely challenge you, if like me, you're a starter!

I really like the pandas library works, i had the little background with R. So learning with this python was quite easy to do it. And also i find it sufficient enough for introduction. Assignment were good to test skill and had fun doing it.

I found this course challenging especially during weeks 3 and 4. In order to pass I had to do a great deal of data cleaning and for this a good knowledge of Python is a must. I highly recommend this course as an introduction to Data Science.

This course is a little bit hard cause you need to do some self training regarding python and pandas. Yet that's exactly what the real world is. So I accepted this style. The forum discussion for this course is very helpful to pass the exam.

Really good course. Provides ample time to figure out things. Does not penalize for slightly late submissions which is good for busy people. Teaches the fundamentals and asks tougher questions in assignments. Does not spoon feed the answers.

This is a great course. A very contentful course.

The best thing about the course is that it's challenging assignments..!!

I had faced a bit of problem in the lectures, as I had to watch the video multiple number of times to understand it..

If you are thinking of doing something in the field of machine learning and Artificial intelligence . If data science is your passin. if you love playing with numbers . if your math teacher is boring , you need to take this specialisation.

Great course, but took a lot longer than I expected to do the homework assignments thoroughly. Instead of 2-3 hours, I usually took 5+ hours. The final assignment took me a really long time because of some technical problems with Jupyter.

Great introduction to doing data science in Python with Pandas. Combined with the later courses in the specialization (the next one is Applied Plotting, Charting, & Data Representation in Python), you will have a strong command of Pandas.

Good course by all standards. The questions are quite hard, and you'd need to read the documentation to find answers to these. I love the program!!! If you just want the certificate without putting in the work, then this is not for you.

Very much challenging course. I just love the way you guys presented and delivered stuff.

Extremely helpful for the further endeavor. I can't wait to continue with the remaining modules.

Special thanks to Christopher Brooks

Appreciated !!

Great course. Well presented videos and relevant assignments.

One small thing on the negative side. The course runs on an older pandas version, you should really upgrade this so we don't have to google "how it was done on pandas 0.19.1"

This course covers basics of pandas dataframes. So useful for amateur/advanced programmers who want to start learning data science. The assignments are very good and help students learn how to pre-process and use data retrieved from web.

A great course! Solid content. Assignments helps you explore and consolidate what you learn.

The autograder could be a bit of nuisance but check out the discussion forums and you should be able to resolve the technical problems yourself.

The difficulty of the excersises made it a good and challenging learning experience. Sometimes it was not possible to continue the rest of the excersises in the assignment if a previous question was not correct, this should be possible.

In the beginning I thought that the course should have more Tips and Help to the student.After finishing it, I understand that having the ability to search for the solution without too helping is good to produce the data science skills.

Great introductory course for data analysis using pandas in python. I have some previous self-taught exposure to python and to pandas, and this was very helpful to formalize my knowledge & approach to analysis in a more structured way.

I learned much in this course, but it's weighted more towards learning Python and Pandas than data science concepts. It was also very time consuming even for someone with programming experience due to the Python/Pandas learning curve.

The course is on some difficult level..But doing assignments is like challenging your self to how much extend you know the programming skills. But we need to spend good amount of time on forums and stack overflow to clarify our doubts.

It is well structured course you will find online about Data Science. All the aspects of a MOOC: like reading materials, videos tutorials, quizzes and assignments are included. Three words for this MOOC: Simple, Elegant and Structured.

I was able to solve the assignments from the discussion and not really from the lectures. I am thinking I should have spent more time reading the discussions (like a textbook) than listening to the lectures. The lectures are too basic

Challenging assignments, prompt response for queries raised in the discussion forum, 5 star for Yusuf for pushing in the direction of the issue without giving out too much, short crisp videos, forces you to refer additional resources.

At first I thought it wouldn't take long because it consists of only 4 weeks but I was wrong! It did't take me a month but definitely more than I expected. Thanks to Coursera and U. of Michigan, I had get to practice a lot. Thank you!

This course of data cleaning is very good. But the tips provided are very high level. It is not easy for a beginner to reach the assignment expectations. I encourage to provide more depth in data manipulation techniques with examples.