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Learner Reviews & Feedback for Machine Learning with Python by IBM

4.7
stars
16,798 ratings

About the Course

Python is one of the most widely used programming languages in machine learning (ML), and many ML job listings require it as a core skill. This course equips aspiring machine learning practitioners with essential Python skills that help them stand out to employers. Throughout the course, you’ll dive into core ML concepts and learn about the iterative nature of model development. With Python libraries like Scikit-learn, you’ll gain hands-on experience with tools used for real-world applications. Plus, you’ll build a foundation in statistical methods like linear and logistic regression. You’ll explore supervised learning techniques with libraries such as Matplotlib and Pandas, as well as classification methods like decision trees, KNN, and SVM, covering key concepts like the bias-variance tradeoff. The course also covers unsupervised learning, including clustering and dimensionality reduction. With guidance on model evaluation, tuning techniques, and practical projects in Jupyter Notebooks, you’ll gain the Python skills that power your ML journey. ENROLL TODAY to enhance your resume with in-demand expertise!...

Top reviews

FO

Oct 9, 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.

RC

Feb 7, 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.

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2776 - 2800 of 2,925 Reviews for Machine Learning with Python

By Катерина М

Jan 28, 2025

Мені треба почати з основ Пайтон

By ARYAN A

May 28, 2023

Could have been more elaborative

By dk

Nov 23, 2019

不建议新人学,这个是系列课程的一部分,内容不多 只讲个大概给你听

By Omkar A

Jun 17, 2019

Practical Classes were Missing.

By David P

Jul 28, 2024

Labs take too long to execute

By Carlos F

Jun 14, 2021

No one answers on the forum.

By aditi m

Nov 18, 2020

Very difficult for beginners

By Scheef K

Nov 22, 2022

beginners, not intermediate

By Philip F

Jan 24, 2019

the tool for HW doesnt work

By MOHAMMED A A A

Feb 4, 2024

Contains outdated material

By Manoj P

Oct 30, 2018

can be done much better

By Rao M H

Apr 1, 2020

Lab are working worst

By Rajesh K R

Dec 12, 2019

Good for beginners

By Сокол С А

Dec 2, 2019

Too superficial

By Ayman

Dec 21, 2024

Special Course

By Bido Y

Jan 9, 2024

not bad,useful

By Anand V S C

Nov 29, 2022

Too simplistic

By Muhammad M M

Apr 7, 2024

Nice course,

By Sumika M

Jan 15, 2022

Good Course.

By fatama j

Oct 31, 2022

good.

By Swastika B

Jun 3, 2022

GOOD.

By SALMA J

Jan 23, 2025

GOOD

By sandra h e

Nov 28, 2023

good

By Akash D

Aug 20, 2020

Good

By Lyn S

Aug 23, 2019

It's too bad some people with phds and very poor teaching skills think they can write up some code and feel they are teaching these classes. That being said, it's super cheap and it's very easy to find information online to supplement the lack of adequate descriptions of the topics. Changes that would make me more likely to take another coursera class :

Don't have a bunch of really short videos, combine them into one longer one.

If there is text or code on a slide, make sure that is in the transcription.

Don't have the dumb popup questions that stop the video and make you find the mouse and click to restart the video. Many of us are listening to the video doing something else, I listen over and over. Sometimes, I have to read the transcription to understand what is being said, so I have to stop, get the mouse, click back up to the slides, press SKIP, etc...

If you have an exam, make sure to later send us the answers - e.g. the code that we were expected to write. This is the weakest and most frustrating part of this class. I was not sure how to some things, in part because I wasn't sure what was being asked, to what detail. Even the class discussions showed we weren't sure what data set to use for what. It seems to rely on peer grading, but most of the responses I got from peers was either completely absent or not useful. But thanks for keeping this relatively cheap.