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.

Short, easy to follow lessons. The labs were very user friendly. The tests were challenging without being too difficult for those beginning data science education.

Great course to learn about open source tools available for data science, highly recommended. Thank you IBM and Coursera for such in depth great learning experience.

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.

I am genuinely chuffed having gone through this course. Clear explanations, theoretical parts well combined with practical ones. Thank you for such a great 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

This course in terms of the contents is good. However, when come to topics regarding line commands for GitHub, it is too fast and cannot learn anything indeed.

This course is easy to understand and as a beginner you can learn the tools pretty effecively. It provides detailed information and the opportunity to explore.

Given sufficient information about the tools were using in datascience. The video explanations are too fast we have to steady pause to get what are instructed.

The course helped me tremendously and enhanced my skill set. I did not know my Keras from my Pyspark before this course but I am now using Pyspark comfortably.

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

The course is very useful. I got introduced to basic programming coding tools like Jupyter Notebook, RStudio, and Zeppelin. Definitely recommend this class!

Awesome course. Lots of Learning. These free sources adds lots of ease to your work, its like everything tool you can think of is present in a single place.