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 Some of the interface was a little outdated compared to the slide show.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.

Its good introductory course but contains very basic things and tasks that are boring and unfruitful to complete (such as the final assignment and many labs that require basic UI skills basically and a lot of clicking).

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.

Every thing is excellent just some videos are outdated like in week 2 there is skill lab in which there is no RStudio in march 2020 but videos shows to complete Rstudio practical. except this this is very good course.

The course is nicely packed. The point i would like to highlight is the 'other Tools part'. The concepts are ok but for a newbie it is not that upto the mark. like the SPSS , it will take time for a newbie to digest.

For getting started to know tools which a Data Scientist uses ,this course is a must, gives a great start since the assignment involves working Jupyter Notebooks, R Studio , Zeppelin Notebooks and IBM Watson Studio.

Muchos videos, en algunos casos ejercicios con imágenes que no corresponden a las actualizaciones de los programas. En general, informa de herramientas muy útiles y da un panorama muy completo de las herramientas.

This course introduces all the tools available in the IBM Watson studio. A brief introduction to every tool is provided and there is a Hands-on exercise for each tool. Overall, a good course for absolute beginners.

Videos prepared to explain IBM Watson tool should be updated. They show IBM Data Science Experience (former ediiton of IBM Watson) and because the interface is not looking the same, tracking the steps is difficult.

So, it wasn't perfect BUT it still was very rewarding in terms of the educational value. Learning to use these data tools will take practice and hands on learning.

The course was well paced and totally enjoyable!

It's a good course. But course videos are outdated. IBM Watson does not operate in the same way as it used to in these videos. And the videos should be updated. As it takes a lot of digging around to figure it out.