Back to Exploratory Data Analysis for Machine Learning

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

4.6

stars

2,516 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

Sep 22, 2021

Excellent, very detailed. However, if the lessons can be expand for hypothesis testing and some of their common test like T test, Anova 1 and 2 way, chi square,..it would be better further.

Apr 24, 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.

Filter by:

326 - 350 of 512 Reviews for Exploratory Data Analysis for Machine Learning

By PRINCE K

•

Oct 27, 2024

awesome

By ADITYA N

•

Dec 6, 2025

kerenn

By Saurabh M

•

May 4, 2025

Better

By rakesh g

•

Jul 26, 2024

thanks

By lucas a

•

Aug 16, 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 5, 2025

GOODD

By WANDA P L

•

Oct 25, 2025

keren

By Tamajit N

•

Nov 8, 2024

Great

By 21_085 R E S

•

Jun 2, 2024

Great

By Mohsen M

•

Feb 3, 2024

10/10

By DAVID R

•

Feb 28, 2022

goods

By William G G B

•

Jan 18, 2022

Good

By Ali A A

•

Oct 27, 2020

great

By Solanki M N .

•

Jan 20, 2026

Good

By NADIA C R

•

Dec 29, 2025

baik

By HARAPRASAD P

•

Dec 23, 2025

nice

By Twinkel D

•

Dec 19, 2025

good

By Shiv O M

•

Nov 30, 2025

Good

By MUHAMMAD H S

•

Oct 27, 2025

good

By Aditi S

•

Aug 18, 2025

good

By Rahul C

•

Aug 16, 2025

good

By Trần M K

•

Jul 14, 2025

good