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

4.6
stars
2,194 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

HV

Nov 11, 2024

With my background on probability and statistics, I think this is a good course, where it can help me apply what i have learned. Not recommend for any one who hasn't taken a statistics course before.

AE

Sep 27, 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.

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376 - 400 of 447 Reviews for Exploratory Data Analysis for Machine Learning

By Rajshree K

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Oct 19, 2022

Very nice explaination....really very helpful

By DONG C

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Sep 9, 2021

Better than other IBM ML certificate series

By Tania L

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Oct 19, 2021

Quite interesting course for beginners

By Vu T T

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Jun 22, 2023

It's a bit difficult to understand

By Chandan K G

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Jul 20, 2021

It was nice learning experience.

By Soumyadip C

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Mar 10, 2024

project submission is difficult

By Aryan T

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Sep 29, 2024

Please elaborate the labs more

By Harsh Y

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Aug 5, 2023

the course is very helpful..

By Shubarani S

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Mar 23, 2024

Its a fantastic platform

By IOVACCHINI F

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Aug 2, 2023

well explained subjects.

By OMAR A A H

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Nov 1, 2020

Very well structured

By Pampa D

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Apr 18, 2022

Good content.

By Harsh P

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Oct 22, 2023

informative

By Agnibha D R

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May 1, 2023

NIce Course

By Gurung K (

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Sep 21, 2024

Buckle up!

By Gautam k

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Nov 23, 2024

good

By AISHWARYA R

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Nov 15, 2024

good

By VAKA C

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Nov 2, 2024

good

By Venkadesh R

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Sep 2, 2024

GOOD

By Ramesha G N

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Jul 23, 2024

good

By PATEL A S

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Aug 7, 2023

goog

By Disha R

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Apr 15, 2024

wow

By Gert-Jan D

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Jul 29, 2022

Potentially this is a great course, but it falls short on a number of points.

* Content is mixed and/or duplicated

* Lab exercises are mostly just demo's. The video's 'explain' no more than you can read in the notebooks.

* The videos show a 'talking head' that is clearly reading the text from a screen. Not very engaging.

* The explanations are not very clear.

It is possible to learn from this course, but then you will have to work on the demo's yourself (deleting the answers first) and read more clear explanations on the topics from other sources.

By Jose J S

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Oct 29, 2024

me parece que el instructor toca temas muy profundos con demasiada velocidad , no profundiza lo suficiente, yo por ejemplo debi invertir muchas horas leyendo complementos en wikipedia , lo que no es ideal pues son topicos muy densos y con mucho contenido matematico. la verdad considero que con este curso apenas logro entender muy superficialmente los conceptos de fondo.

By Eric J B

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Mar 27, 2024

I was disappointed by this course. The initial portions that focused on Exploratory Data Analysis were ok, but I thought more tools and techniques would be explored. As we progressed into hypothesis testing, the content got progressively weaker. It seemed like an attempt to cover some basic material but without the depth to be truly useful.