I felt the Jupyter notebook and Markdown portion was more highlighted than the others. Could have been made much more better, but I am grateful for even the little that I learnt. I would sincerely like to thank the course instructors.

Very clear explanations

Though I feel assets used in tutorials must be provided in order to have step by step and success rate.

I found myself getting stuck when uploading my own datasets and the jupyter notebooks returned with errors.

Some videos need to be polished a little better to be more understandable. Specially the ones where people walk you through coding and using tools: they go a little bit too fast for people like me who know nothing about this subject.

This course is very beneficial for beginners. As the instructor teach you how to use Data science tool such as Jupyter Notebook, Zeepline Notebook, R Studio etc.

One thing i fill that the teaching sense is not that good for beginners.

Interesting but sometimes shows lots and lots of tools that you won't been using during the course. Fewer tools taught in a more significant way like doing labs would be great. It does a good job in making you use Jupyter notebooks.

Esta muy bien pero los estudiantes de coursera no tenemos acceso al IBM SPSS version para estudiantes, Coursera es una empresa potente y se que puede conseguirlo. Agraqdeceria que si lo consiguiesen ame avisen para poder utilizarlo.

Very good course, if you are hoping to use the IBM set tools, but stills it gives you a perspective of whtat to expect whereas using this kind of tools, although you need to know a little bit of programmig to fully aptreciate it,

There is a lot to learn here, and some parts of it are very information dense. I am just very glad that we are able to study this at our own pace.

Overall, I am happy with this course and look forward to the starting the next one!

An informative course, which shows some of the basics for Python, R Studio and more.

BUT, the week 3 videos are a disaster, as the change to Watson Studio has not be reflected in the current videos, generating lots of frustration.

Nice and good course. The only thing taht could be better is the alignment of the video's of Data Experience of IBM with the current IBM Watson environment. There are some major differences. But nevertheless very good training.

This course has really high quality. I gained a sense of what data scientists use in their daily life. But it is a little confusing when knowing about a lot of tools for the first time. It takes time to get familiar with them.

Some parts of this course could be better organized to help learners. For example, the GitHub exercise in terminal should have previous concepts about using terminal in Linux, like how to create a directory or how to navigate.

Useful course with programs I wasn't familiar with. Class was laid out nicely for me to follow along and pass the assignments. Some of the interface was a little outdated compared to the slide show. Other than that well done.

I found it to be a bit confusing when the course materials for older versions of the tools were used to teach the current versions of the tools. There were differences beyond just the name (Data Science Experience vs Watson).

Difficulties to finish the last two without the ability to create an account on IBM Cloud, nevertheless remains a good introduction about tools for data science (I imagine it's a excellent one if you can create the account).

Useful course to learn the basics, but some upgrade would be great. Some videos are old and the user interface of the platforms has changed. That makes following the videos complicated and the learning process less enjoying.

This course covers the most useful and relevant tools and libraries for Data Science, helping newcomers to learn fast and well guided. However, the trial that IBM offers at the end of its 3rd Section is no longer available.

It was a challenging course with some heavy usage of terminology. It took a little while to get my feet wet but the Lab sessions and reviewing content/videos helped and I was able to complete all my assignments succesfully.

As I am used to emacs as my go-to software for programming, given it's intense extensibility, I will keep using it instead of the other tools.

In any way, it was great to know more tools oriented torwards group programming.

Some of the IBM tool videos (Data Refinery in particular) is kind of hard to follow, it was like jumping into the deep end of the pool. Could've been better is it was a bit slower and had a lab session to go along with it.

I think the course was good overall giving the gist of various popular open source platforms available for Data Science. The only thing which disappointed me was that the course was not updated from a long period of time.

The course was amazing, I was more than happy to find out that there are easy ways to perform the tasks of data science in environments that are ready and perfect and I'll definitely use them.

Thanks a loT Coursera and IBM

At some point, I felt somewhat frustrated trying to open a Watson Studio account. Unfortunately, I couldn't with my debit cards but skipped the huddle using open-source tools like Jupyter. The experience is bitter-sweet.

Amazing experience with this course learn new tools like IPYTHON, Ibm watson , all these tools are very well explained by tutor.But the think i dont liked is this is python course so why you add Rstudio in this course.

Good course, but the videos should be updated, for example, it shows IBM Data Science Experience when the name changed to IBM Watson Studio. Some links changed position in the screen and I lost time trying to find them.