Just enough to know the different types of open source tools that can be used to data science. to learn the tool completely, we need to refer to many tutorial materials within.

Good Introduction session for tool applications.

The course is exceptionally good in order to introduce you various details about the tools that you require for Data Science Analytics.

Exceptionally well made support by IBM and Coursera is as a whole best for these courses.

The overview reagarding the tools for data science is very good. It has covered many insights and classification of tools that a data scientist can utilize and also make note of such tools to work effectively with the data.

Great course and the tools provided are very useful. You have to really work by yourself to read and understand the tools though, because there is no way other than practice to learn the various notebooks and how they work.

I am novice to this field. Nevertheless, I did not have much troubles in catching up the class because the contents of this courses are very well organized and the level of the class was well adjusted. Thank you very much!

I loved the practical approach of the course. It's not just listing of tools but step by step application which makes me more confident-I know exactly where to fetch each tool I need in a Data Science Project.

Thank you.

The Tools which were mentioned in the course are really helpful and important.

Through this course, you can get to know about various tools used in Data Science with their use and explanation. I really liked this course.

Though the interface in the videos were little outdated, the IBM professionals are working on it to make it better. The style of teaching is incredible. Extremely responsive team. Thanks for giving us a chance to learn.

Ofrece un contenido bastante detallado de las diferentes herramientas para la ciencia de datos, no solo para el procesamiento y la ejecución de código, sino entornos colaborativos útiles y muy usados en la actualidad.

I am grateful that the internet have Coursera, a platform to spend my time learning something new. After following the second part of this course, I am excited to continue to the third part of it. Thank you Coursera!

this was a very good course, to kick start the basics of various IDE's and how to use them on the cloud. This course is very helpful in providing knowledge and outlook of many new technologies that i am not aware of.

The course provides a healthy introduction to the tools used for data science. I appreciate the engaging nature of the content which encourages one to understand how the tools work and to try them out for practice.

I really enjoyed this course! I had a very poor knowlegde of Zepplelin for instance, now I even consider using that tool more often! Besides, learning how to better use Jupyter is a great experience worthy the time!

I did learn something about Data Science tools but not thoroughly. Hope to learn further on the tools and its application. I know now that IBM Watson Studio is great to do Data Analytics. Thanks to the instructors.

Some videos are of inferior quality. And subtitles at times inconsistent with what people in video are saying. Also in R lab some insonsistencies, such as the code that should be added in the end is already added.

Excellent content for someone who has no programming background! I will recommend to anyone to sign up cause even if you might doubt that you don't know much, by the the end of the course you will feel like a Pro!

This course introduced me to the open source tools available for data scientists. The good thing about this course is introduction to multiple tools rather than a single tool and exercises to practice on the tool.

Great hands on introduction to using Python, Rstudio and Jupyter notebooks. Definitely an important first step and a welcomed changed after the first course was mostly memorization of random data science facts.

This course has given me basic understanding of tools used in data science and its uses. It has given me confidence that folks who don't have computer science background can also master the data analysis skills.

This track has exposed me to tools i never knew existed as a beginner, I have learnt how to use them and I am pleased to have gone through the track, my gratitude to my teachers and IBM for putting this together

We get to learn the basics of all open-source data science tools and their working in IBM Watson Studio and IBM Data Science Workbench. Tools we learn here are Jupyter Notebooks, Zeppelin Notebooks, R Studio IDE

I have learned much knowledge about data science. And there are so many tools and programming languages to deal with it. They are useful and Intelligent and i have more interest to join the data sicence world.

An amazing course providing great exposure to data science basics and tools for data science. The amazing explanation regarding the benefits of the cloud computing in the world of data science are dope as well.

I enjoyed learning about these tools available for Data Science. This introduction did some to show the capabilities but would need more study and use to master them and learn more capabilities of these tools.

Nice Course, You can have a look at all data science tools we can use for different tasks of data science..

And how IBM Watson Studio integrates all tools at a single place and makes data scientist's life easy.