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

26,039 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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3301 - 3325 of 4,251 Reviews for Tools for Data Science

By Andy C

Jun 29, 2020

I am ready to have more hands on experience, the overview of IBM products seems much to long. I would rather learn about the products doing more hands on exercises.

By Ray C

Feb 22, 2020

The Watson studio training was poor and dated. The Watson interface was poorly constructed and not intuitive or user friendly. I prefer Pycharm and Rstudio to Watson

By Prachi S B

Apr 22, 2019

It was difficult to get Watson Studio working initially. Faced many issues. And created almost 3 different accounts to get it working. Lost 3 days of time in that.

By Liang S

Jul 27, 2019

The DSX video is very out-dated, I was pretty confused and frustrated while trying to follow the video guides. The R-studio map function was pretty cool though.

By Chinami A

May 8, 2019

What tutorial video shows and the user interface (IBM Watson studio) look different so that it was confusing sometimes. The tutorial videos need to be updated.

By Charles K

Apr 7, 2020

Content is good. Videos need to be updated very soon. In the middle of the course I was confused because the videos are so much different than actual websites.

By Ashish D

Dec 22, 2019

Good course.

Unfortunately none of the opensource tools are leveraged in the subsequent courses.

All the subsequent courses will mandate you to use IBM products.

By Haitham M

Feb 24, 2020

The videos are a bit outdated, especially in week 3. There is no resemblance between the current version of Watson studio and what is explained in the videos.

By Robert I

May 1, 2019

It was fun to learn new data science tools. The third week was sometimes frustrating because the course videos did not match with the layout of Watson Studio.

By Sebastian T

Aug 7, 2020

Some of the classes seem rushed, especially during Week 2. It can cause confusion and some fear to attendants. Week 3 picks up the pace again, and was great

By Lasse C L

Jul 29, 2022

A bit heavy on IBM tools, many of them may never be relevant. Some video's are pointless, some the quality is poor. Especially the github videos er rubish.

By falowo g

Aug 19, 2021

i feel the material focus a whole lot on ibm products which i understand.But it kind of sucks you in for longer periods whenits meant to be a brief intro.

By Andrii

Apr 29, 2021

Git and GitHub could be explained better - not possible to understand from info given in a course, you have to go and search for extra information outside.

By Phubet C

Mar 6, 2021

There were some parts. It's too much details about name of another package and brand name of it or something. Really difficult to digest it in a few hour.

By James P

Sep 25, 2020

It was a good basic overview across a range of topics. The assignments were very, very easy however; I don't think it was particularly challenging at all.

By Everett T

Jun 30, 2019

The instructions are not very clear and also the interface for IBM Waston has changed a lot but the videos have not been updated, which caused confusions.

By Jay P

Sep 4, 2020

The content was not so much helpful for someone who is learning the data science, Rather it was more like the pitch of IBM Watson, especially 3rd module.

By Mingshu L

Mar 22, 2020

too basic... and it's really weird that I have to submit so many times for quiz until it feels less of a learning experience but more of a bug experience

By Bhavya K

May 10, 2021

I felt that the course wasn't thorough - it seemed more like an endorsement for IBM Watson more than an attempt at teaching data science. Disappointed.

By Katarina S

Dec 8, 2019

Not all learning materials are up to date. I needed to invest significant amount of time to understand how to create New Project in IBM Watson Studio!

By Cole M

Dec 4, 2019

A little too easy (only took an hour or two) and navigating IBM's Watson is confusing at times. Overall though, this course delivers what it promises.

By Maxime C

May 12, 2019

Ok intro - just light on underlying technical details and probably requires a background into coding to really get good insight into tools and uses.

By Александр А

Dec 22, 2018

Didn't like this module cause all this Open Source tools could be mentioned in 1 short video lection and then learners should learn the specific one

By Katie B

Oct 22, 2018

It was informative. However, it seems outdated. The module for Rstudio is basically useless because it n longer works in data Scientist Workbench.

By Oluwaseun S O

Feb 20, 2023

A lot of demonstrations and tools spoken about. Would have been nice to have some practical exercises to solidify knowledge gained from the module.