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Learner Reviews & Feedback for Tools for Data Science by IBM

4.5
stars
29,112 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

DE

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.

MO

Apr 17, 2023

the best course for the beginner who is going to start his data science journey. This course tells you all options like tools, libraries, programming languages, etc. Highly recommended for beginners.

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2751 - 2775 of 4,751 Reviews for Tools for Data Science

By Chairul A

Jan 19, 2020

Great intro course for the open source tools. However, would be better if there's an optional readings/tutorials for installing some of the tools directly on PC.

By Miguel O

Jul 29, 2019

Some of the options in the videos are no longer available as explained in the DSX Platform, but after looking for them a little I was able to complete the tasks.

By Amanzhol K

Jan 17, 2019

I didn't like because it was based upon previous version of the website. I think it would have been better if the course was up-to-date with the website version.

By Ganesh N

Sep 23, 2023

In my peer graded assignment of this course, total marks assigned is a 25 on 25 by the peer reviewer, but Coursera calculates it as 23 on 25. is there a reason?

By Xing W C

Apr 27, 2022

Very informative, but lack of practice materials. IBM should provide more optional practices for students to work more with the knowledge taught by this course.

By durchfalle

Apr 25, 2020

I enjoyed the start, I docked one start because i would have liked to have seen more even though i knows it is a building process my hunger for more made do it!

By Ross T

Feb 17, 2020

A great overview of the key open source tools out there - I've used RStudio and Jupyterlab in the past so was expecting these, Zeppelin was a pleasant surprise.

By Vitor C

Feb 10, 2020

It's a good course to know more about commons tools that might aid Data Scientists. However, it needs an update on the names and interfaces shown on the videos.

By Katherine N

May 20, 2022

This is an informative and well-done course, but the videos and articles need to be updated to match the current interface on IBM Watson Studio and IBM Cloud.

By Ariel S

May 21, 2020

The course and content were good. I did find quite a few typos in the content and some of the videos were so outdated that it was challenging to follow along.

By Anuar M

Feb 21, 2020

This course need to update the Week3 tutorial as DSX has been replaced by IBM Watson. The example and tutorial are different from the actual lab by IBM Watson

By Manuel A N R

May 8, 2020

Easy to understand and enables you to keep learning about this tools. They have to update some of the videos, because some names and some interfaces changed.

By Pradnyapal M

Mar 5, 2020

Its very good to know about the industry tools in the data scientist field where we use multiple languages using in one studio to integrate the programming .

By NaturallyMe D

Nov 28, 2023

New to Data Science, it started out a bit intimating. The instructions made it easy to follow. Excited to have completed the course with limited set backs.

By Charles J

Mar 27, 2020

Actually videos about IBM Watson Studio just describes the former edition instead of present one, so it can be really confused to practice as in the videos.

By Rafale C

May 20, 2019

Course material didn't update for IBM Watson Studio, makes learner spent super huge time to check the difference between material tutorial and real website.

By Matheus C M

Dec 12, 2022

Good introduction, but a lot of information that seems not important and/or applicable at this moment. It will probably be revised in other future moments.

By srustisuman m

May 31, 2019

overall very informative, loved it. just a suggestion, please renew the IBM watson videos because they are quite old and different from new interface there

By Adil W

May 24, 2019

Some online tools provided for course where not working properly, many times they failed to open and Rstudio in IBM Watson Studio failed to install library

By Madhavendra S N

Nov 20, 2023

Nice Course, the certificate seems to have ome worh but the material is pretty simple,maybe because i have already made some projects with help of youtube

By Anurag P

Sep 5, 2020

A great way to learn Jupyter Notebook fundamentals if you are new to it! IBM Watson suite is bit rushed but I believe that's the way it is supposed to be.

By Alireza M

Jun 9, 2022

It was a well managed course, Although it would be better to give me a choice whether I want to do the excercises in platforms other than Watson Studio.

By MANTRIPRAGADA K C

Aug 10, 2020

After completing the course, I got an idea on the tools that are used in Data science and also the hands-on learning helped a lot in improving the skills

By Alix H P

Jun 8, 2020

Good review--I enjoyed coming up to speed quickly withe IDE for Jupyter notebook using Python. So much easier to debug code based on the "cell-structure"

By Mitchell C

Dec 15, 2019

The steps the video has you walk through and the actual platform are slightly different which can be confusing. Overall, great introduction to the tools.