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Learner Reviews & Feedback for Machine Learning with Python by IBM

4.7
stars
17,901 ratings

About the Course

Python is a core skill in machine learning, and this course equips you with the tools to apply it effectively. You’ll learn key ML concepts, build models with scikit-learn, and gain hands-on experience using Jupyter Notebooks. Start with regression techniques like linear, multiple linear, polynomial, and logistic regression. Then move into supervised models such as decision trees, K-Nearest Neighbors, and support vector machines. You’ll also explore unsupervised learning, including clustering methods and dimensionality reduction with PCA, t-SNE, and UMAP. Through real-world labs, you’ll practice model evaluation, cross-validation, regularization, and pipeline optimization. A final project on rainfall prediction and a course-wide exam will help you apply and reinforce your skills. Enroll now to start building machine learning models with confidence using Python....

Top reviews

RV

Jan 14, 2025

good course , some part is typical more statistical part shown, even i have good understanding of ML , so new learner will find little typical. rest tutor voice and language is understandable.

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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2526 - 2550 of 3,176 Reviews for Machine Learning with Python

By Mitanshi K

Apr 30, 2020

Great for beginners. Explains theoretical concepts well but lags on the coding part of it.

By Vinit K S

Apr 8, 2020

It is such a vast topic, It would have really been great if there were few more exercises.

By Ritesh P

Dec 4, 2023

Random Forest, XGBoost etc should have been there. Decision tree explanation was amazing.

By Daniel J B O

May 26, 2020

A little bit to basic for someone who studied the topics in the past but a good refresher

By Mauricio C

Jul 11, 2024

Hace falta que se explique mas los cuadernos de laboratorio para entender mas la teoria

By Rubén G

May 29, 2020

I recommend including more examples and documentation of the metrics in the algorithms.

By Aldy P

May 29, 2020

This course didn't help Much for a beginner. But overall worth to try. Thanks Coursera!

By Asanka W

Aug 23, 2022

Good course great explanation, but i had issues with practicles overal course is great

By Stefanos S

Dec 18, 2020

If the last assignment was a bit easier regarding the Hypothesis Testing would be 5/5.

By Sudhir S

Dec 2, 2018

More videos would have helped to understand concepts of subject better to apply in lab

By Sanjiv S

Apr 24, 2025

I'm very satisfied with this specialization course. I upgraded my skills in AI and ML

By Robert F

Aug 2, 2020

The final test portion was a little rough. Finally got the test to work successfully.

By anas m r

Aug 2, 2020

A great introduction for ML, but you have to exert effort to understand the lab codes

By Meijuan Z

Mar 22, 2020

Should include more details of ML algorithm, but is nice to people who are new to ML.

By Miguel A M

Sep 8, 2025

Demasiada estadística para los programadores, me ha costado mucho algunos conceptos.

By Ammar S

Sep 2, 2024

Overall is good. Maybe improvement in terms of simple introduction to deep learning.

By Sadabrata K

Mar 22, 2020

Random Forest Classifier is not included. Everything else is very good. Nice course.

By Devraj S

May 1, 2020

It will be more helpful if this course has a more detailed explanation of the codes

By Eden P

Apr 11, 2020

Really enjoyed this one. Quite challenging in places however rewarding nonetheless.

By HUSENI N G

Mar 19, 2020

VERY GOOD SYLLABUS & COURSE MATERIAL

VERY GOOD SUPPORT FROM COURSERA SUPPORT TEAM.

By Naomi R

May 16, 2022

Great course but it would be good if it covered the preprocessing of data as well

By Dhaivat P

Apr 19, 2020

It is a very good course and the instructor is so good you get code to practice on

By Eric B

Jan 20, 2020

Good introductory course covering most of the basic ML algos. Wish it covered NLP.

By Labib F

Apr 23, 2025

A great course indeed. Gives a clear idea about algorithms and evalution metrics.

By K A N D U L A V E N K A T A H E M A N T H

Oct 4, 2020

This course is very hepful to build a carrer and update yourself with the skills