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.

This course is too complete, but have too many questions between videos, its feels like a brake every time, I think is more easer at the end of the videos.

The course content is really great and method of teaching is very specific .Much details very covered during the course and really i gained a lot from this.

Good course if you are beginning data science. You don't need much of python experience but will be better to have if you want to quickly finish the course.

One of the difficult courses among other other data analyst course. But the hands on labs in this course are the best tools to understand the concepts !!

Very detailed and guided course that provides an overview of data analysis in Python with short assignments after each video and interesting lab courses.

insufficient statistic, as the name of the course is Data Analysis, i would expect more classes about the different distributions of data, pdf and pmf..

One of the best courses in the IBM Data Science Specialisation.

I would like to have more quiz questions and opportunities to practise what was covered.

There must be a slightly high level of Quiz, assignment and Project and must have to add some more advanced concepts about statistics and probability.

I would have given it 5 stars but they barely went over polynomial regressions and pipelines and it was a major portion of the end of class assignment.

pros: well organized, clearly explained each step, useful

cons: frequent errors in both videos and the lab, especially on the questions part in the lab

Final exam was too complicated. I have 2 masters degree and for me it was clear, but for other it is too complicated.

P.S. it is my personal opinion

Course is good, but in this short course it is covering lot of thing thatswhy lot of topics are just touched intead of going little bit deep into it.

You learn a lot, good intro to data science with python. Labs have typos and can be confusing at times though, the only thing that could be improved.

A very interesting and easy course. Anyone can catch up with big concepts with little effort. Thank you Coursera and IBM for this wonderful course.

Course is nicely designed and pare explained well.

I would have liked to see the steps along with the final answer to the peer assignment questions.

Very good course. I wish there were more hands on exercises. We only had a chance to practice in one lab per module; otherwise, I learned a lot.

Great course to start learning python applied to analysis, but after this, I prefer to use R. Less complicated and can obtain the same results.

The course material is good. However, I found the videos a bit fast and the automated audio speech is not so good. The lab sessions are great.

I find this course useful. But some of the contents are little advanced all of a sudden and feels some important explanations are not covered.