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

4.6

stars

1,633 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 26, 2021

Very detailed course of Exploratory Data Analysis for Machine learning. Ready to take the next step in data science or Machine learning, this is great course for taking you to the next level.

Sep 21, 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.

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226 - 250 of 337 Reviews for Exploratory Data Analysis for Machine Learning

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

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Jul 11, 2022

Excellent

By ABHIJIT B

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Jan 25, 2021

Very good

By Vitor R

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Nov 24, 2020

Awesome!!

By OMKAR N C

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Feb 22, 2024

All Good

By Rohit K

•

Jan 14, 2021

good one

By lucas a

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Aug 15, 2023

gooood

By Shruti Y

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Feb 28, 2023

useful

By Hariom K

•

Jan 18, 2022

Thanks

By Sathisha

•

Aug 3, 2021

got it

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 GUDITI J B

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Feb 29, 2024

Nice

By Chonchal k

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Dec 31, 2023

good

By Shivani S

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Oct 23, 2023

good

By Avijit B

•

May 27, 2023

well

By Nurlan I

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Mar 25, 2023

s cd

By NIMALAN P

•

Feb 4, 2023

good

By KASIREDDY A

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Nov 17, 2022

GOOD

By Sabina S

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Oct 19, 2021

Good

By Miguel B D S N

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Jan 26, 2021

Nice

By nuriddin z

•

Nov 10, 2023

yes