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.

A great opportunity for middleclass student to jump in Data Science filed

i am very thankful and humble to all of Coursera team they develop a amazing training system

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.

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.