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

4.6

stars

2,545 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.

Jul 17, 2025

More example in simplified way could help new learner to understand. Overall I really like this course. This help us to crack some of good area where I need to re-work .

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326 - 350 of 516 Reviews for Exploratory Data Analysis for Machine Learning

By Rohit K

•

Jan 14, 2021

good one

By MD T I

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Jul 18, 2025

awesome

By Sourav K

•

Nov 7, 2024

awesome

By PRINCE K

•

Oct 27, 2024

awesome

By ADITYA N

•

Dec 5, 2025

kerenn

By Saurabh M

•

May 3, 2025

Better

By rakesh g

•

Jul 25, 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 IZZAT I

•

Dec 4, 2025

GOODD

By WANDA P L

•

Oct 25, 2025

keren

By Tamajit N

•

Nov 7, 2024

Great

By 21_085 R E S

•

Jun 2, 2024

Great

By Mohsen M

•

Feb 3, 2024

10/10

By DAVID R

•

Feb 27, 2022

goods

By William G G B

•

Jan 17, 2022

Good

By Ali A A

•

Oct 26, 2020

great

By Tsoy M

•

Jan 29, 2026

dads

By Solanki M N .

•

Jan 19, 2026

Good

By NADIA C R

•

Dec 29, 2025

baik

By HARAPRASAD P

•

Dec 22, 2025

nice

By Twinkel D

•

Dec 18, 2025

good

By Shiv O M

•

Nov 29, 2025

Good