Pretty dry material. Hard topic to teach since the process really comes from experience. Could stand to focus a bit more on ways to explore and clean data. Not bad though.

The lab is good for learning, the quiz i think should be add more questions, too small, overall is ok for the beginner for learning the data analysis with Python, thanks.

very good course, it's getting harder in W5,6 and it was hard to understand, I think that the instructor could be more informative about topics discussed in these week .

Good introduction to the things one can do with Python and Pandas, but overall fairly basic and does not require the students to actually program something of their own.

Good for a first course in data analysis however this course covers the subject on a very superficial level. There are a few errors in the assignment's solution guide.

Good but in the end of the course specially week 4 and week 5, speed of information providing in videos get to very high speed comparative to other weeks information.

For a Beginner data science ,the entire course is very helpful.Though some portion of the course needs more clarification about the topic,but overall I am satisfied

The course provides a complete guide for beginners to start data analysis. but mostly it provides a rough overview of concepts so we need to learn in detail manually

Some of the topics at the end of the video have been rushed to end. I would rather liked to see an elaborate examples for those topics to atleast have an idea of it.

185/5000

It requires more technical skills and knowledge in other areas not mentioned like python or IBM platform.

However this has done push me to learn more skills.

I could have used a little more explanation when it came to Pipelines and Polynomials, but I figure there will likely be more of that to come in the later courses.

The course is a good start for beginners. The course contained everything useful form churning of data to regression. Pretty decent explanation with practice labs.

Good For Begineer approach to Data Analysis with Python .. Data Visualization with python is more understanding about visualization experience after this course .

Great coverage of fundamentals. Seems to be missing some content around diagnostic metrics for classification problems (e.g. binary class) using AUC/ROC curves.

The course is well organized and the content is presented is an accessible manner. Exercises could be more challenging and cumulative to help increase retention.

Most of the course is very easy to understand, although the exercises in the notebook can become complex, the exercises do not always run and must be done again.

Fun course! Lots of interesting content. It could've been more interesting and challenging with addition of a couple of marked assignments or a capstone project!

The course material is great enough for a beginner. However, some of the presentation method is confusing. The narrator also seems like a laymen for the course.

Great content, but awkward, untimely popping of questions during video lectures, very annoying. Labs are very useful and productive, but videos are too short.

This Course was very informative and beneficial and conceptual too, being newbie i personally feel that this course has taught me alot. Thanks to team Coursera

Muy buen curso, por mejorar: varios errores en los talleres y también no fue posible ingresar a estos durante varios días lo cual atrasó el proceso de estudio.

I love how engaging the course is with its labs and how it is well-packaged in such a manner that encourages beginners to learn... keep up the good work guys.

I found this module very difficult to understand as it was loaded with high end concepts and coding. Might have to redo this course to understand even better.

Course content is very good but I feel it can be more improved if the training is provided at slower pace. Also the examples should be in detail. Overall good

I think it would be good if the units had activities to deliver mandatory since that would allow to strengthen the knowledge acquired. Thanks for the course.