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Learner Reviews & Feedback for Tools for Data Science by IBM

4.5
stars
29,295 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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3776 - 3800 of 4,789 Reviews for Tools for Data Science

By Kushal J

Jun 25, 2021

The course was more focused on listing various tools and a brief on them and with not zero experience and knowledge on data science jargons, made this course less effective.

By David E

Apr 9, 2020

I felt like some of the information on tests was never covered. Same is true for some modules. Overall, learned tips though. The cheat sheet for coding is extremely helpful.

By Joseph A

Jun 6, 2023

Despite it helping better understand what are the tools used in data science and how I can use the, the speaker's voice felt so robotic that made it harder for me to focus.

By Huy P N M

May 20, 2021

Typical marketing course :))), unless you are aiming for a professional certificate, I don't recommend this course at all, cause you learn nothing besides IBM software :)))

By Pauline S

Jan 4, 2023

Very basic. You learn what tools exist but not really how to use them. Also, too much emphasis on Watson, even though I understand that IBM wants to promote their product.

By Mek T

Jun 20, 2020

Not very organized course, a lot of stuff plugged in a module and because of that frustrating to learn. On the positive side, I like module 2 on Git and Jupyter notebooks.

By Nora S I

Dec 3, 2018

I liked the course, a good overview. Unfortunately, I had such a hard time with the last task: not because of its difficulty, but technicalities using IBM Watson Studio.

By Utkarsh S

Mar 29, 2022

I think this module should have more reading material. because there are too many technical terms which are just explained in a hurry which makes ti difficult to grasp.

By Jonas F

Nov 12, 2019

The data platform's name and handling has changed, which makes it more difficult to create the accounts and follow the instructions. The instructions should be renewed.

By Jakub C

Mar 27, 2020

There are some videos which are not updated and IBM Watson doesn't really work as described in scripts and videos. Project parts completely missing for some settings.

By Nelson C

Dec 9, 2020

It is a course for very beginner to know what kind of tools that they may need to use for data science. And it is also an advertisement of IBM for their data service.

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.