course was ok. Sometimes the requests to download resources would not work which made the jupyter notebooks partially useless. The instructions videos were very fast.

The exercises on the Watson cloud were too complicated to set up, I guess that could have been solved quite easy via a Jupiter notebook. Everything elase was great.

Good introduction to Python. But it would be better if it demonstrated the use of API's in a practical way (Like, what can one do with the results he/she gets).

Course content is good, however the Watson Studio partsare dominated by the platform complexity instead of the content and the guides/screenshots are outdated.

Some good content and good explanations in the videos, but the final project is really unclear and focuses more about using IBM software than coding in Python.

For this course, I think it is good in general, because it covers some fundamentals regarding python, however, it needs more practice questions in my opinion.

It's more a course about development, data manipulation and a bit of webscrapping/API. If you already some notion in data science, you will not learn a lot

It would have been beneficial to be learn more about building a dashboard visualization. That part of the quiz/test that I had trouble with for some reason.

You could have made this course longer, for example separate week for pandas and numpy, and web scrapping

Also, there should have been a week for matplotlib.

Fairly good course, but a terrible assignment. This assignment was not testing what we learned but added all sorts of fairly irrelevant different issues.

Some of the instruction at the end of the course was not very helpful and there were some errors with information or links. Overall it is a good course.

The last part of the course seemed a bit hurried. Not enough practice exercises on "pandas" and "numpy" libraries. A bit disappointed with the course.

Дается очень мало информации, только общее представление о необходимом программном обеспечении. Нет серьезных заданий для самостоятельного выполнения.

I wish there had been alittle more assistance when I needed it, some things are implied, and therefore can take longer if not explained appropriately

Labs need to be improved. There should be excercises for students to complete by themselves and more explanation in the videos on difficult topics.

Thorough for the time period. However, some knowledge was inferred when doing the labs instead of building on top of knowledge taught in the lessons

Good course but very superficial, in order to truly create skills to find a job more projects may be needed per course to truly master the concepts.

A fast paced course. Good in some ways. But I feel the course is missing a lot details. And there are waaaaaaaaaay to much typos for a coding course

class is not that much challenging

but it's okay maybe this is for beginner

but IBM lab tutorial needs some effort to let user use it in daily work

I hoped to have learnt a bunch more stuff on programming in python.

It was a nice start though. Full with some nice and practical tips and methods.

The hands on projects are too easy. They need to be a little more creative. They also don't go deep in the details of a new function/library ...

Advice to someone newly learning phython "Start from somewhere else!" even tho course is good but it's also too small in terms of explaination.

Most of the projects on IBM cloud had errors working with them. Overall, course was a good introduction to Python for Data Science application.

Trés bon cours en terme de comprehension, parcontrel es exercices Quiz sont parfois banal, je propose qu'on y ajoute un peu plus de complexité.