Very interesting and hands-on course. Especially with the assignments not being timed and instead being allowed to google, but the assignments still being appropriately hard. The assignments promote problem-solving on the fly and finding the help you need on stackoverflow, google, etc.

This course is excellent if you're looking to learn how to use Pandas inside Jupyter Notebooks. Assignments are autograded and feedback can be received immediately. Course is a few years old and discussion forums contain answers to common questions

Great introduction to applied data science. The weekly assignments are challenging and varied, and students are required some independent studying outside of the lessons. The forums are also quite helpful in approaching the assignments.

I'd say it is a very robust course for pandas intro, particularly the coding assignments are excellent! I consider this my stepping stone to becoming a competitive data scientist. Michigan's courses are always of high-quality.

Really impressed by the material and quality of instructions to teach this complex topic. I felt the assignments were appropriately challenging to apply concepts taught in the lecture. Well done and thank you!

The assessments, quizzes, and course coverage are quite good. The main points are covered, although it does not cover everything. Additionally, it provides opportunities to learn and conduct research.

It's very useful specially for new learner because it only dives into the part of python that data science need. I strongly recommend to anyone even if you don't have experience in programming before.

Um curso intenso e bastante prazeroso. Gostei de todas as etapas, os videos funcionam bem e estão construidos numa base introdutória, mas o desafio é pesquisar e pesquisar. Muito interessante mesmo!

the course is designed very well. It covers data manipulation topics very well. It has excellent assignments which help in understanding the course concepts more better

Frankly, I did not watch the lessons at all, although they seem good.

The assignments were really great !

Challenging and very rewarding.

Really recommend the course !

Very interesting course to guide you through from the basics of pandas. Teaching staff is of great help throughout the learning process, with speedy replies.

Great course that teaches about how to process data in Python. The lectures are very code-based and the programming assignments help you learn new methods.

Excellent course with assignments, But some elaborated videos on topics could help much better in solving the assignments in time.

Prof Brooks, Yusuf and Jimi have worked out engaging but also demanding applied course on the subject. Thank you very much

Discussion forums are very useful. Exam questions are challenging for beginners but doable. Good teaching.

Great course, but expect to really work. The assignments force you to get a good grasp of the material.

Excellent course if you are interested in start learning about Pandas, and data handling in general.

Excellent course! The professor is super clear and the content was really well organized!

Very helpful and practical course, great intro to data science.

This is the only course worth in the specialization

Great course to bulild strong base on Pandas.

i am so happy

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It took me a while, but I finally figured out the problem with this class. The lectures provide some good information, but only rarely do they go into WHY a particular action/method/approach is used or WHY it will be important later. I had to do my own deep dives into available documentation to figure out how most of the functionality covered in lectures really works. This is not necessarily a flaw in the class, but it does mean the suggested time commitment for each week of class is significantly underestimated.

The assignments, while interesting, have the same issue as the lectures. Most of the time is spent using of Google to look up Pandas and Numpy functions or methods, or if we really get stuck, to see if someone on StackOverflow already addressed any questions you might have.

Put simply, the only different between this class and learning from a book is the class sets deadlines for the students to meet in the form of graded assignments.

Of course, the setting of deadlines is an excellent way to stimulate learning, and this is why I will continue on with the Data Science specialization.

The course will teach you basics of the Pandas library, which is an essential skill. It also gets involved with some issues related to data cleaning, which is also essential, but felt a little like

There is very little peer-to-peer learning because there are no practice sets that peers can talk over, only assignments which Coursera's Honor Code naturally prohibits discussing. Hence, the learner never sees optimized code for solving real-world problems. I'm pretty sure I would have learned more if this course had provided more practice problems for learner discussions. For example, very inefficient iterations can be used to solved problems that should be solved in better ways with Pandas. I know that sometimes I was doing it right, but I think sometimes I wasn't and it would have been nice to see better code.