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Learner Reviews & Feedback for Tools for Data Science by IBM

4.5
stars
29,176 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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3126 - 3150 of 4,765 Reviews for Tools for Data Science

By Kevin D

May 24, 2019

A bit repetitive on the IBM Watson piece but a good overview nonetheless.

By Pedro V d A

Sep 9, 2023

Deu para ter uma boa noção e experimentar alguns conceitos. Vale a pena!

By Ankit

Jul 14, 2023

I enjoyed the course because of the detailed information provided in it.

By manoj b

Mar 27, 2022

Course was fine, but videos could have been more better and interactive.

By Manjeet K

Aug 26, 2021

that is good but it wants more improvement in modules to identify easily

By Ajinkya K

Sep 19, 2020

Videos could be longer to help folk who have zero programming knowledge.

By Fidel B C B

Jun 4, 2019

Cuesta trabajo el ejercicio porque no esta cual como indica el ejercicio

By Deleted A

Apr 9, 2019

IBM Watson related content needs to be updated and be more comprehensive

By Omar A

Mar 30, 2024

Excelente curso, buen contenido, muy explicativo y todo bien organizado

By Eliza S

Jan 24, 2024

A good chapter to understand all useful DS tools. Which are new for me.

By SHUO T

Oct 3, 2020

Week 2's quality should be improved, make it more friendly for beginner

By Juan P E C

Jun 17, 2020

Good course, explanation about Git Hub could have been more detailed...

By Shuyuan C

Jun 17, 2019

Very interesting course and you can learn a lot about Jupyter Notebook.

By Ahmad S

Mar 6, 2020

Please update the video content to suit the updated IBM Watson Studio.

By Alexander T

Jun 30, 2019

Gives the idea of where to go and how to start using some tools for DS

By Vasu S

Jun 4, 2021

It's a good course but we need more detailed videos on Watson Studio.

By Christopher D

May 13, 2021

It was a lot of information but a good primer for the specialization.

By Karim A

Jan 6, 2020

Please update the vides to reflect the same environment as IBM Watson

By Filipe S M G

Aug 18, 2019

Interesting to know the available tools (although, a bit repetitive).

By Samantha R

Jul 8, 2019

Nice starting point to learn how to use a notebook in a simple manner

By Joe A

Jun 30, 2019

Good introduction to various tools available to data science novices.

By David P

Jun 13, 2019

An exciting start to the actual work of data science using IBM tools.

By Humayun A

Apr 20, 2019

need to explain what we will learn from this week materials and quiz.

By Navaneetha K R

Apr 4, 2019

Course gives a overall view of how to use various data science tools.

By asher b

Sep 14, 2018

Succinct high-level overview. Still need more courses to get skilled.