This is a very good introductory level course to know about various open source tools for data science. It gives idea about R, Python, Jupyter Notebook, Zeppelin etc

This part of the course is interesting and I did learn how to use some new tools, but for most of it, it was almost a sales pitch. Saying that, I do love IBM Watson.

Overall is good, but in the last module which require student to participate in IBM watson studio have a lot of problem such as notebook creation on watson platform

I particularly liked the chance to practice with the online tools. The only caveat was that I missed some of the unstructured "work with your own data" exploration.

Course content needs to be updated in case of IBM Watson, there's so much buzz about it. Video tutorials are absolutely inconsistent with the actual UI of the tool.

Week three videos need to be updated, Enjoying the content, but the use of the old videos made the last lesson or two harder to follow than was strictly necessary.

An interesting introduction. Some materials are slightly out of date, so know you might have to dig around in the IBM webGUI, but very well laid out none-the-less

It gives an awesom idea of what kind of tools can a Junior Data Scientist use, in order to learn about it. Nevertheless, some of the chapters are a few repetitive.

Most of the modules were very great. I would have loved to see those question prompts but there were none. It wasn't easy keeping a steady attention to all videos

It would be helpful to have some extra videos explaining to explain more in detail functions in each of the programs. Apart from that, the content is quite good!

Great intro course for the open source tools. However, would be better if there's an optional readings/tutorials for installing some of the tools directly on PC.

Some of the options in the videos are no longer available as explained in the DSX Platform, but after looking for them a little I was able to complete the tasks.

I didn't like because it was based upon previous version of the website. I think it would have been better if the course was up-to-date with the website version.

In my peer graded assignment of this course, total marks assigned is a 25 on 25 by the peer reviewer, but Coursera calculates it as 23 on 25. is there a reason?

Very informative, but lack of practice materials. IBM should provide more optional practices for students to work more with the knowledge taught by this course.

I enjoyed the start, I docked one start because i would have liked to have seen more even though i knows it is a building process my hunger for more made do it!

A great overview of the key open source tools out there - I've used RStudio and Jupyterlab in the past so was expecting these, Zeppelin was a pleasant surprise.

It's a good course to know more about commons tools that might aid Data Scientists. However, it needs an update on the names and interfaces shown on the videos.

This is an informative and well-done course, but the videos and articles need to be updated to match the current interface on IBM Watson Studio and IBM Cloud.

The course and content were good. I did find quite a few typos in the content and some of the videos were so outdated that it was challenging to follow along.

This course need to update the Week3 tutorial as DSX has been replaced by IBM Watson. The example and tutorial are different from the actual lab by IBM Watson

Easy to understand and enables you to keep learning about this tools. They have to update some of the videos, because some names and some interfaces changed.

Its very good to know about the industry tools in the data scientist field where we use multiple languages using in one studio to integrate the programming .

New to Data Science, it started out a bit intimating. The instructions made it easy to follow. Excited to have completed the course with limited set backs.

Actually videos about IBM Watson Studio just describes the former edition instead of present one, so it can be really confused to practice as in the videos.