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IBM による 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.


Tools for Data Science: 1951 - 1975 / 2,648 レビュー


Jan 30, 2020

nice course

by Caio L

Sep 21, 2019

Too simple.


Feb 11, 2019

Haaa heavy

by Satishkumar M

Jan 04, 2020



Oct 24, 2019

well done

by Axel L

Sep 27, 2019



Mar 23, 2019

very good

by Debakanta S

Feb 04, 2020

its okay

by Mohd S B B

Dec 20, 2019


by Akash K M

Nov 25, 2019

loved it

by yelamanchili v r

Jun 16, 2020


by Farah R

May 18, 2020


by Md. M R K

May 30, 2020



Jun 25, 2020


by Prashant H P

Mar 29, 2020



Feb 20, 2020


by Krishna K

Sep 01, 2019


by Yangala R G L S S K R

Jul 08, 2019


by Aswanth V S

May 09, 2019


by Nigel D

May 27, 2020


by Karen J M

Aug 07, 2019

The basic content was helpful, especially for a beginner. However, it is imperative that the videos be updated to match the current version of Watson. They now show a defunct DSX environment that is very different from the Watson environment being used. One of the videos that the course analytics labeled in a "helping" pop-up comment "Was the most visited and considered important by learners" was the confusing outdated doubt this was the actual reason learners played it over and over trying to make sense of it, not because it was especially valuable for learning. Another suggestion: many of the videos or reading material used a lot of jargon and DS terms as if they assumed that learners already knew these terms. It would be helpful to have an online glossary for each course with short definitions of the terms that are thrown around casually in the early videos, and sometimes defined later in the course (or maybe will be in later courses in the certificate), but that many learners are not familiar with at this point.

by Christopher D

Apr 10, 2020

The actual course content was fine, but the link they used for accessing the software rarely if ever worked. It continuously showed essential software required for the course as "coming soon". Literally hundreds of students were reporting this problem in the discussion forums, but the only instructor feedback was "clear your cache and try again". Which was a not only a solution that had no bearing on the server side cloud environment features, but in many instances made the situation worse.

My only feedback is to PLEASE PLEASE make sure the software environment is working, and to PLEASE take student comments that they cannot access the environment seriously and propose real solutions. In the event that the environment is simply not usable, please suggest other methods of working through the material- IE, how to install Jupyter and Zeppelin on our local workstations.

by Rebecca V O

Jan 11, 2020

The course is ok but materials need to be updated to reflect latest changes to IBM tools, so that students don't waste time trying to find things while setting up and accessing tools. Also, could help to include more info with realistic examples or a few interview blips with real data scientists on when they use one tool over another- real context. LIke, why use Jupyter Notebooks over Zeppelin or IBM environment - the course addresses these at high level but I think perspectives from real people in the field what they're really using, and how it solves their day to day issues and workflows is a needed addition to the course to make it more immediately useful.

by Diego M E C

Jun 28, 2020

There's a huge area of opportunity here to improve the content of the lessons, or most likely the way it is presented to the students. If you visit forums of week 1 and 2, you'll find a lot of discontent from the students. Even though the lessons content is good, the way it's introduced to the students is not the best. I'm only giving three stars to create awareness of this particular issue. In my personal opinion the course was ok, I understand it's just a glance of the several tools one can use for data science but if you're curious enough you can take enough advantage of the course's content. Great tools presented and a lot of self learning left to do.

by Niraj D

Jan 17, 2020

The Course was good but it could have been much better if it was based on Video tutorials. It was really difficult to understand the written instrustions for me initially as in to how to perform some of the codes which we had to execute just by reading the insturctions given in the course readings. I had to refer some of the videos from youtube to understant some of the instructions, so had been the course explained through video tutorials it would have been much better to understand the module. The module was good it was just that the study material was a bit tricky and time consuming to understand due to the absence of video explations.