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Open Source tools for Data Science に戻る

IBM による Open Source tools for Data Science の受講者のレビューおよびフィードバック



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!!!!


Feb 01, 2019

All the tools required for ML kick starting was explained very clearly and it helped me a lot in building the understanding of what tools need to be learnt in the field of ML and Data Science.


Open Source tools for Data Science: 26 - 50 / 1,022 レビュー

by Khadija S

Dec 03, 2018

Excellent for beginners

by Venkata R S

Dec 20, 2018

Simple and Quick Overview of the tools

by Sushant G

Dec 08, 2018

vERY Good

by Ashok K

Dec 20, 2018

It is a good course. Lot to learn about Data Science. There is a small problem at times. Like the IBM Watson Studio instruction do not match with the actual website. BUT this minor small problem is easily over come. As I am discovering. The IBM's website is being upgraded for GOOD REASONS. SO even if there is some mismatch in their video instructions, no problem !!! One can find newer relevant answers on Google search or on FORUMS. Which is very good in learning to overcome minor difficulties. So Overall VERY GOOD as I am also learning.

by Ahmed F

Dec 20, 2018

Well explained!

by Satyam C

Dec 08, 2018


by Srikanth P

Dec 09, 2018

One thing, the promo code did not work for me. Most of the options on Watson studio are new. Please review. Thank you.

by Tobiloba F A

Dec 08, 2018

I had fun doing the assignment

by Jesus C C

Dec 23, 2018

great introduction! very easy to follow

by Mohamed F

Dec 24, 2018

This course is really good and give basic ideas about various data science tools viz Jupyter notebook, zeppelin, R Studio IDE, IBM Watson Studio etc.,

by Said E I

Dec 25, 2018

Very good introduction.

by Naveen K

Dec 25, 2018

Cool Learning content with deep understanding..!

by Michael B

Dec 12, 2018

Great overview and application of some of the tools required for data science projects.

by Avoaja U c

Dec 13, 2018

Very informative course, It offers a gentle introduction to machine learning. And IBM has provided tools worth thousands of dollars for free to learners.

by Ivo M

Dec 12, 2018

Very good overview of Tools and platforms to use!

by Moez B

Dec 25, 2018

Very basic stuff, but a well-organized course.

by ThangarajDeivasikamani

Dec 31, 2018

Nice to learn more open source tools

by B R P K

Dec 31, 2018

Great Course

by Mateusz K

Jan 01, 2019

Nice review of existing open source tools and free to use web services implementing those tools. Personally I would also enjoy some introduction to either how to set up those open source tools on a personal computer or private cloud.

by Saptashwa B

Dec 31, 2018

Very good course ! But I would love to have a bit harder assignments!

by Shahbaz K

Dec 31, 2018

It was great :)

by Rajeshree S

Jan 02, 2019

Good introduction to the various platforms for practicing data science. I liked the peer graded assignment of this course.

by Chris G

Jan 02, 2019

Excellent introduction to relevant open source tools used in Data Science.

by Abhishek J

Jan 28, 2019


by Lawrence K M

Jan 27, 2019

Good introductory course