It would be very helpful if there were notes for each video that contained the code discussed -- both for the sake of learning, but also for people with visual impairments who might not be able to see the code in the videos

such a wonderful course threshold for students, Indeed i got some idea about data science and what's the data science domain dissertation within python . Eventually this course gave me conception and notion of data science.

Hay preguntas mal redactadas y preguntas que tienen más de una solución que te afectan en el examen final. el curso en general fue bueno, pero pienso que podria ser mas friendly para los novatos o un poco mas intectactivo.

Great, but some of the labs could be edited for better grammar and descriptions. Could not complete some of the Watson labs because my api keys would not work for some reason and I did not know how to go about fixing that.

The curriculum is too good.But at final stages it became complicated and started to confuse.Felt that there could have been a little more documentation to make understand at the final 2 weeks.But great course.Learnt a lot.

The inner workings of the project (dashboard creation process) are not that clear. May be an optional reading can be added for interested students to understand the dashboard creation and the libraries used in more detail.

Understanding the Final Assignment and its instructions were a bit tricky. May be an introduction to IBM cloud hosting and the significance of various credentials required in the final assignment will make it a bit easier.

Clear and accurate. The last part (APIs, HTTP, ...) is a bit confusing, it goes quite fast and some elements are repeated. Overall, great course to set the baseline for the future courses of the different specializations.

Friends, The course is above my expectations. Very good. Just two comments. I would need an aposila to better follow the video explanations. And some exercises were not running in Jupyter Lab. Still the course is great.

the only issue I had is the codes are written on white board itself , difficult to understand what is the input code, instead u can show that on a code editor.(distinguish between codes and theory explanation) -thank you

A fair foundational course. Week 5 could have a more meaningful assignment e.g. correlation, not just plotting. The last (not rated) part of the course, uploading your results into the cloud, needs a proper explanation.

Week 5 final project did not have clear instructions about how to navigate through IBM Watson Studio. Took me a while to figure that out. Otherwise, the course is pretty good and the exercises are very straightforward.

Very good for getting started with Python. But looks like the interface changed since the tutorial video/instruction have been made so it caused some confuse. It'll be better if you update those tutorial/instruction.

Overall I think the course was a useful introduction to python programming for data science, and the tools and workbooks were super helpful. The instructions could be a bit more clear, but it wasn't enough to stop me.

Lots of great foundational learning, but in the later sections some pretty massive leaps in instructional logic. Perhaps meant to give the learner a taste of what is possible, but also a little overwhelming. Thanks!

Over all I enjoyed the course very much but there were gaps in the course materials that we struggle to complete the assignment. Perhaps this could be addressed during the practice sessions in the weekly course work.

The various plug in locations and environment we use in the course could be better explained. It appears to be an on line IDE with a python interpreter running. Hard to get views of the lab as you are doing them.

This course allowed me to learn the basics of the Python programming language and how to apply it to real life problems and data. Very much recommended if you wish to acquire these basic skills. Good job, Coursera

Good introduction to Python for data science. The quality of teaching materials is ok, the examples used are not very useful or inspiring. You will come away with a few Jupyter notebooks for future code building.

The materials are okay, but more exercises are needed to help students get more hands-on experience. Also, a lot of instructions are complicated and seem to be outdated (technical details on using IBM Watson lab)

The course is perfect for me, because I already know Python (so I can skim through material quickly just review the data science related stuff) but to people new to programming, this course may be going too fast.

The course gives a good Introduction to working with Python. Minus 1 Star because the final assignment relies on a given block of code, instead of being a project, which one can solve just with what was learned.

Some of the video modules didn't have up-to-date information, but the labs were very helpful. The IBM Cloud services were slightly challenging to configure. The Cognitive Class Labs tools were very easy to use.

Fort intéressant. Cependant, il y a plusieurs fonctions qui sont simplement données dans les laboratoires, sans qu'elles soient expliquées.

J'ai dû faire des recherches pour comprendre à quoi elles servaient.

Few things could have been better like more explanation for complete beginners. This course is still great for all the exercises and content. I am now taking it again to understand it better. Thanks Coursera