学生对 IBM 提供的 Tools for Data Science 的评价和反馈

This course creates a friendly environment to learn Jupiter notebook, Zeppelin Notebooks, RStudio and IBM Watson Studio step by step.

Course materials and assignments are great!!

I was really excited to dealing with IBM Watson Studio through the Internet. Also, given IBM Badge made me feel very worthwhile about learning. Thanks for this practical lecture.

The information is clear and allowed me to complete all the activities, just be aware that the IBM tool is not upgraded in the course so research and web navigation is mandatory.

Once I enrolled in this course I had no idea about Data Science tools. This course is the best for who don't know anything in Data Science tools and very beginners in this area.

An invaluable hands-on provision. I feel as though I am adequately hatted with the basic skills and equipped with the efficient tools for my next steps in pursuing Data Science.

I would like to thank you for the good structure the course has and of course the material is very well explained. It lacks nothing in terms of content from an in class course.

I learned about a lot of tools that I hadn't heard before. The course walks through deep insights into IBM Watson Studio and every aspect of it. This is a very detailed course.

intimidated to learn the analytics tools and worried i was too much of a beginner to take this course on. It was very easy to follow the steps 1 by 1 to learn these tools.

I use a chromebook and these tools were very helpfull for someone who is new to the discipline and cannot reliably boot a python terminal or R studio on his primary machine.

This was a fantastic course. I managed to learn a vast set of skills in both Skills Network Lab and IBM Watson studio. I recommend Coursera to all of my friends and Family.

Great course for understanding the essentials tools required to implement Data Science. Juypter Notebook and Zappelin Notebooks are the most preferred Notebooks to work on.

Brief introduction to manny useful online tools for data science. Although it seems to be easy to accomplish this course, it really helps me learn more about data science.

This course is primordial to meet the tools applied to the slim courses. Explicit concepts and ease of access in the course. Course clear, structured and of great value.

It was a great experience!! I had a great time learning how to create a new project, then a notebook where you can write codes using Markdown Cells, Headers, HTML,etc.

Makes you familiar with the software tools needed to write code in Data Science. It is not an programming class but rather a great tutorial around each piece software.

Thanks a lot to Coursera & mentors. I am really very happy for such a wonderful teaching pattern which is not only beginner friendly but interesting & interactive too.

I learned how to use Jupyter Notebook in the IBM Data Science Experience and practically with its proficiency in preparing a notepad along with the Markdown recording.

Useful tools for the beginning data scientist. However I found that all courses listed through this specialization are available for free through Cognitive Class Labs.

Very nice introduction to online tools with simple hands on training. Labs and quizzes are build the confidence of the student whether novice or expert in other areas.

Loved the practical exercises and information. Hands on in the notebooks in a few different environment gave me confidence to try out other things on my own. Thanks.

This course is little tough to clear at Assignment Stage but if your curious and determined then it's just the matter of time and you will start loving DATA SCIENCE.

Thanks for creating this course but while doing it with complete specialization according to first course it feels little hard and not connected with previous course

its a bit challenging for a fresher in computers but with help of faculty support that is compensated .Special thanks to Miss Mallika...I could complete the course.

This course help me as beginner to understand about tools for data science such as rstudio, IBM cloud to create notebook and how to create simple code using phyton

Nicely documented learning. Only suggestion is to update the content of lab where instructions are per the old DSX tool and are not exactly same for Watson studio.