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Learner Reviews & Feedback for Exploratory Data Analysis for Machine Learning by IBM

4.6

stars

2,439 ratings

About the Course

This first course in the IBM Machine Learning Professional Certificate introduces you to Machine Learning and the content of the professional certificate. In this course you will realize the importance of good, quality data. You will learn common techniques to retrieve your data, clean it, apply feature engineering, and have it ready for preliminary analysis and hypothesis testing. By the end of this course you should be able to: Retrieve data from multiple data sources: SQL, NoSQL databases, APIs, Cloud Describe and use common feature selection and feature engineering techniques Handle categorical and ordinal features, as well as missing values Use a variety of techniques for detecting and dealing with outliers Articulate why feature scaling is important and use a variety of scaling techniques Who should take this course? This course targets aspiring data scientists interested in acquiring hands-on experience with Machine Learning and Artificial Intelligence in a business setting. What skills should you have? To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Calculus, Linear Algebra, Probability, and Statistics....

Top reviews

Apr 23, 2024

The course includes hands-on exercises that allows us to apply the learned EDA techniques to real-world data. This practical approach helps solidify my understanding.

Nov 30, 2020

The only reason that I do not give it 5 stars is because the website of coursera is not good enough to handle the peer review assignments at the end of the course.

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301 - 325 of 494 Reviews for Exploratory Data Analysis for Machine Learning

By Himanshi S

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Oct 5, 2024

excellent

By SUBROTO M

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Sep 20, 2024

Excellent

By Ignacio R J

•

Aug 1, 2024

Excelente

By Victor M C

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Jun 5, 2024

very good

By Ghizlane A

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Sep 13, 2023

thank you

By VICKY K

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Apr 29, 2023

AWESOME!!

By PRAVAT P

•

Apr 8, 2023

Wonderful

By Sri A K

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Mar 8, 2023

Loved it

By Molini U

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Jan 18, 2023

excellent

By Rohit Y

•

Jul 11, 2022

Excellent

By ABHIJIT B

•

Jan 25, 2021

Very good

By Vitor R

•

Nov 24, 2020

Awesome!!

By Jhosep S L C

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Sep 2, 2025

ok check

By OMKAR N C

•

Feb 22, 2024

All Good

By Rohit K

•

Jan 14, 2021

good one

By MD T I

•

Jul 18, 2025

awesome

By Sourav K

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Nov 7, 2024

awesome

By PRINCE K

•

Oct 27, 2024

awesome

By Saurabh M

•

May 4, 2025

Better

By rakesh g

•

Jul 26, 2024

thanks

By lucas a

•

Aug 15, 2023

gooood

By Shruti Y

•

Feb 28, 2023

useful

By Hariom K

•

Jan 18, 2022

Thanks

By Sathyaraj P

•

Aug 3, 2021

got it

By WANDA P L

•

Oct 25, 2025

keren