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

4.6
stars
2,445 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聽 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 聽 Who should take this course? This course targets aspiring data scientists interested in acquiring hands-on experience聽 with Machine Learning and Artificial Intelligence in a business setting. 聽 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

AP

Feb 26, 2023

This course was amazing. I always assumed that EDA was the challenging part of ML, But in this course I found it so cool. can't wait for the next course.

ML

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.

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By Tamajit N

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Nov 8, 2024

Great

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Jun 2, 2024

Great

By Mohsen M

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Feb 3, 2024

10/10

By DAVID R

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Feb 28, 2022

goods

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Jan 18, 2022

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Oct 27, 2020

great

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Oct 27, 2025

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good

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Mar 21, 2025

Nice

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Feb 7, 2025

imba

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Feb 5, 2025

good

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Dec 21, 2024

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Dec 10, 2024

good

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Nov 25, 2024

good

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Oct 31, 2024

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Nice

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Sep 15, 2024

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Sep 7, 2024

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Feb 29, 2024

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