I found the course to be informative and covering a variety of tools. However it was constructed in a superfluous manner. I wish the material had more examples and was constructed in a little more detailed manner.

I thought the class was good and well organized. Polong Lin was very good. The only downside is that the video was dated when it came to IBM Watson studio. That was a bit confusing. But manageable. Thanks again.

Most of the videos were very good and easy to understand. But the videos of DATA REFINERY and many videos on GITHUB were hard (or near impossible) to understand. Please do make them in an user-friendly manner.

This course was really helpful. It gives you insight for the data tools used now days. The only reason I did not give it 5 stars is because the video is not updated as per the creation of project in IBM Watson.

Very educational course. However, the interface on the videos are quite different from that of cognitive labs or IBM Watson. This made site navigation very difficult.

All in all, it was a good one. Learnt a lot.

Muy buen curso me ayudo bastante que tengamos las herramientas disponibles en la plataforma de IBM solo que algunas se han actualizado y los videos no, pero solo Rstudio IDE y Experiencia de Ciencia De Datos

Loved the course and learnt a whole new world of information. Some questions in the quizzes are not worded correctly (especially one in the final quiz at the end of the course, these need to be corrected).

I enjoyed it and learned a lot. My only criticism is that the quiz questions can be misleading and/or they ask about something that hasn't been covered yet or an aspect of something that was never covered.

Need to update guideline for IBM Watson Studio. I spend lot of time myself to figure out how to use the latest IBM Cloud. However, it is quite an amazing course to have R, Python & Scala in an environment.

A good introduction to the tools used in Data Science. I consider that Git usage can be applied to almost any software project, not only to Data Science. The quality of the GitHub section is not too good.

Much better course that "What is Data Science". Actually introduces the tools to be used in DS. However, could go into more depth for Jupyter Notebook, python and R, and leave out the IBM stuff in Week 3.

I learned a lot from this course. It forced me way out my comfort zone. However, some of the videos need to be updated. Some of the videos had Data Science Experience interface rather than Watson Studio.

This is a good course, but need some update. The transition from week 1 to week 2 is a bit confusing and there are mentions to old names no longer in use.

Overall, I really liked and learn a lot. Thanks!

+: Important content providing insight into the instruments of a data scientist.

-: Very superficial introductory course. A student who completed this course cannot yet master any of the tools introduced.

This is a very good course. But some videos are not updated. As the IBM Data Science Experience has updated to IBM Watson so the video should also updated. It takes a lot of time for me in the IBM Watson

I've subtracted one star since the videos, especially in week 3, were not in synch with the online tools (IBM Watson Studio). Otherwise, this was a good class for intro to open source data science tools.

Tools are fantastic and will make a significant contribution to my education. Videos need to be updated for changes to Watson Studios. Support from IBM on their cloud services should also be improved.

Great course, would have got 5* if the videos were based on the new platform, as it was tricky in some areas to relate back to the newer version after looking at the old interface in the video demos. :)

The course video contents and the tools versions are not the same.There are some significant differences .Videos should be updated.In general the course is a good fundamental course about the tools.

The course contents are verry good and well structured except that Watson Studio tools and services options need to be explaind more, specially those used in the lab steps or explained in the videos.

i rather to chose what is data science is better in perspective of materials and assignment, because in tools for data science i feel a lot of boring because to much explanation for what have to use

Some of the lab assignments had instructions that didn't line up with how the programs actually worked. This was particularly the case for modular flow where auto-numerics seemed impossible to use.

Gives you a good idea and overview about different tools but can be overwhelming because of the amount of new information and some videos are not up to date. Week 3 especially had some weak videos.

It would be nice if you could update the material since some tools have changed either name or the way they look compared to the videos/images. Very good material though, I enjoyed the course much.

A good presentation and initiation to the tools for data science. A little hiccup on the fact that the course should be up to date with Watson Studio that hasn't exactly the same interface. Great !