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学生对 IBM 提供的 Open Source tools for Data Science 的评价和反馈

11,492 个评分
1,445 个审阅


What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you'll learn about Jupyter Notebooks, RStudio IDE, Apache Zeppelin and Data Science Experience. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. With the tools hosted in the cloud on Cognitive Class Labs, you will be able to test each tool and follow instructions to run simple code in Python, R or Scala. To end the course, you will create a final project with a Jupyter Notebook on IBM Data Science Experience and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....



Apr 25, 2019

To the contrast of other reviews, I find the content very well bifurcated and fed to the learners. The course very easily digestable and I have had a great amount of fun learning it.. Go for it!!!!


Jun 30, 2019

This course is very nice to understand Python, Zappelin and R Studio basics on code and concepts, in which you will get hands on along with creating a free IBM Cloud and Watson Studio account.


251 - Open Source tools for Data Science 的 275 个评论(共 1,431 个)

创建者 Siripat W

Oct 31, 2018

It's excited to know another text editor but jupyter notebook, thank you

创建者 Anette F

Nov 04, 2018

Great introduction into Open Source Tools and into the basic workings of these tools. I love the labs, this is so hands-on and really gives the most realistic view on data science tasks and how they are done that I have come across so far.

创建者 Dheerendra S

Nov 03, 2018

Great course to use open source tool.

创建者 Abhimanyu S

Nov 04, 2018

Very nice course. This course gives a detailed introduction to the IBM Watson Studio along with other important tools for Data Scientists. It's a must do course for all beginners in the field of Data Science


Nov 06, 2018

Thank you!!

创建者 Somaiya J G

Nov 06, 2018

Amazing, before this course I was only aware about Jupytor notebooks, this helped me a lot.

创建者 Arturo B

Nov 07, 2018

Excelent for start to use this tools.

创建者 Carlos J B A

Nov 07, 2018

The courses I have taken have served me for my professional life, expand my knowledge and apply them finding results. This undoubtedly marked my personal life feeling happy and calm with what I am living. I feel that this platform has changed my life because it has ended with many paradigms that I had with respect to education, thanks to the financial help that Coursera has given me I have been able to move forward in my life project. Thanks you very much. Greetings from Colombia

创建者 Sandeep T

Nov 08, 2018

Great learning experience. Thanks to all trainer and my peers for sharing the knowledge

创建者 Ahmed T

Nov 08, 2018

Amazing :)

创建者 Shaleen S

Nov 12, 2018

Provides a good overview for first timers.

创建者 Néstor R V M

Nov 12, 2018


创建者 reza M

Nov 13, 2018

zeppelin notebook was wonderful!

创建者 Fulufhelo

Nov 14, 2018

Very informative course

创建者 Abhishek M

Nov 15, 2018

Watson exp is awesome, I am happy to see IBM SPSS Modeler there

创建者 Luis E D M

Nov 15, 2018

keep me in context of the tools used for doing datascience

创建者 Lee W A

Nov 16, 2018

good (gentle) introduction into IBM Watson environment.

创建者 Rubén J R G

Nov 25, 2018

This. Course gives you all tools you will need to be a data scientist


Nov 18, 2018


创建者 Hector G

Nov 20, 2018


创建者 Petko V

Nov 19, 2018

Course content was good. May want to consider updating some of the videos as some of them do not match with what the IBM UI looks like now.


Nov 24, 2018

Great course!!!

创建者 Spataru N

Oct 06, 2018

Exactly what you need

创建者 Jamiil T A

Oct 06, 2018

Awesome , i love what an incredible online open soure for data scientist. Let's do something.

创建者 Eric G

Oct 07, 2018

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.