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Learner Reviews & Feedback for Machine Learning with Python by IBM

4.7
stars
16,409 ratings

About the Course

Get ready to dive into the world of Machine Learning (ML) by using Python! This course is for you whether you want to advance your Data Science career or get started in Machine Learning and Deep Learning. This course will begin with a gentle introduction to Machine Learning and what it is, with topics like supervised vs unsupervised learning, linear & non-linear regression, simple regression and more. You will then dive into classification techniques using different classification algorithms, namely K-Nearest Neighbors (KNN), decision trees, and Logistic Regression. You’ll also learn about the importance and different types of clustering such as k-means, hierarchical clustering, and DBSCAN. With all the many concepts you will learn, a big emphasis will be placed on hands-on learning. You will work with Python libraries like SciPy and scikit-learn and apply your knowledge through labs. In the final project you will demonstrate your skills by building, evaluating and comparing several Machine Learning models using different algorithms. By the end of this course, you will have job ready skills to add to your resume and a certificate in machine learning to prove your competency....

Top reviews

RC

Feb 6, 2019

The course was highly informative and very well presented. It was very easier to follow. Many complicated concepts were clearly explained. It improved my confidence with respect to programming skills.

FO

Oct 8, 2020

I'm extremely excited with what I have learnt so far. As a newbie in Machine Learning, the exposure gained will serve as the much needed foundation to delve into its application to real life problems.

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2376 - 2400 of 2,858 Reviews for Machine Learning with Python

By Arriouach M

•

Apr 19, 2024

Good experience, I have learned, more skills about ML.

By MOHIT Y

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Oct 18, 2021

If You are a beginner then don't start with this course.

By Jan J Y

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May 18, 2021

Some issues with importing libraries using the notebooks

By Brendan W

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Apr 8, 2020

Excellent course, lots of typos in the lab instructions.

By AVIJIT S G

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Sep 1, 2024

Great But Not the Best. But still better than the rest.

By Kshitij G

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Nov 16, 2021

Good Intro of ML algorithms for beginners/intermediates

By Thomas

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Jun 26, 2020

This is a good course I wished it was more challenging.

By Abdul M A

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May 14, 2019

very good lecture but not detailing notes to back it up

By Agrim R

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Jun 27, 2022

please provide vedios for python code explanation also

By VISHAL P

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Jul 27, 2020

this course was amazing for statistical field student

By Jayant D

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Jul 29, 2019

Explanation is good but code practice could be better.

By micheal k

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Feb 14, 2023

great course

although short, many things are discussed

By Javier G R

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Apr 10, 2023

I would like some bibliography for deeper knowledge.

By Rafael M S

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Feb 14, 2023

Very good courser but some videos are too much long.

By NANDINI J 2

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Jan 21, 2023

The course is well-arranged. Perfect for beginners.

By Penumarthi S R

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May 24, 2020

I would highly recommend people to take this course.

By Mohammad P

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Feb 1, 2023

Great content and hands on lab to grasp the concept

By Vithushan V

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Jun 19, 2022

Very Good Course. I really enjoy my final project.

By Pokkunuri S C

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Nov 28, 2019

All the videos and practice exercises are wonderful

By Hassan B

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Oct 22, 2019

I enjoyed this course. It contains a great content.

By Zach H

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Feb 25, 2024

Could use more extension materials/further reading

By هاني ا

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Feb 20, 2022

Some video need to be updted , else its v.good

By Rafi O

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Jun 21, 2020

Great course. Some errors need to be fixed though.

By Benjamin L

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Oct 30, 2019

The final assignment was not as good as I expected

By Veeram R S S

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Jun 21, 2020

it would be good if there were coding assignments