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Learner Reviews & Feedback for Tools for Data Science by IBM Skills Network

25,766 ratings

About the Course

In order to be successful in Data Science, you need to be skilled with using tools that Data Science professionals employ as part of their jobs. This course teaches you about the popular tools in Data Science and how to use them. You will become familiar with the Data Scientist’s tool kit which includes: Libraries & Packages, Data Sets, Machine Learning Models, Kernels, as well as the various Open source, commercial, Big Data and Cloud-based tools. Work with Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. You will understand what each tool is used for, what programming languages they can execute, their features and limitations. This course gives plenty of hands-on experience in order to develop skills for working with these Data Science Tools. With the tools hosted in the cloud on Skills Network Labs, you will be able to test each tool and follow instructions to run simple code in Python, R, or Scala. Towards the end the course, you will create a final project with a Jupyter Notebook. You will demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers....

Top reviews


Aug 14, 2022

I love the detailing of every aspect of this course. The Labs, the free subscriptions and free trials provided by IBM Skills Network, everything has been so amazing. Thank you Coursera, thank you IBM.


Apr 12, 2020

It serves perfecty its aim that is giving a first glance of the open course tools for data science. Of course each tool is briefly touched and it hands over the student the duty to deepen each tool.

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326 - 350 of 4,178 Reviews for Tools for Data Science

By Abdul H

Jun 9, 2020

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.

By Devvrat M

Dec 1, 2019

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.

By 陈嘉琪

Aug 27, 2019

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.

By Tassio C d A G

Feb 24, 2019

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.

By P D

Apr 12, 2020

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.

By Zaheer R

Oct 14, 2019

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.

By Nikhil K

Jan 25, 2019

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.

By Glener D M

Jan 22, 2019

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.

By Andrew B

Jan 6, 2019

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.

By Gopala R

Oct 3, 2018

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.

By Alpesh G

Jun 8, 2021

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.


Mar 24, 2020

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.

By Raghupati Y P

Feb 22, 2020

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.

By Pinky C

Dec 11, 2019

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

By Diana J

Jul 13, 2020

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.

By Agata

Jul 31, 2021

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!


Jun 28, 2020

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

By Vivekanand P

Sep 11, 2019

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.

By Ramon M

Apr 19, 2020

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!

By Yasmin

Apr 19, 2020

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


May 9, 2022

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.

By Senthil K T

Aug 4, 2022

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.

By Abdulkadir G

Mar 6, 2022

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.

By Min T A

Feb 14, 2021

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.

By Mina W

Jun 23, 2020

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.