Comentários e feedback de alunos de Tools for Data Science da instituição IBM

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.

Great course! I learned about so many open source tools for data analysis. I also learned how to use these open source tools at a basic level. FOUNDATION SECURED!

Clear and easy to follow course. very rich in resources and self-learning materials to sharpen your knowledge even if totally new to programming and data science

I gained a lot of valuable information with regard to the tools and scope of data science. With that, I now have more confidence in my data science profession.

I enjoyed this level a lot and am astonished by the capabilities of the Watson Studio. I am really glad that I can finally find my way on these powerful tools.

I found this course very useful. I especially enjoyed practice with new markdown tools in Jupyter which were very useful for creating well formatted notebooks.

As elementary as it could be, it's a great introduction to Jupyter Notebooks indeed. But starting from this, I could see farther the reaching of Data Science.

São muitos recursos e um mundo de ferramentas. O curso passa pela mais relevantes e propõe atividades práticas em cada uma delas. Muito bom ter este panorama.

Informative course: the course introduces Jupiter Notebook and R Studio. Good start to learn more about programming languages that are used in data science!

A great course especially for starting with Jupyter Notebook, Zapellin or R studio. IBM Watson Studio is definitively the most crucial aspect of this course