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Learner Reviews & Feedback for Supervised Machine Learning: Classification by IBM

319 ratings

About the Course

This course introduces you to one of the main types of modeling families of supervised Machine Learning: Classification. You will learn how to train predictive models to classify categorical outcomes and how to use error metrics to compare across different models. The hands-on section of this course focuses on using best practices for classification, including train and test splits, and handling data sets with unbalanced classes. By the end of this course you should be able to: -Differentiate uses and applications of classification and classification ensembles -Describe and use logistic regression models -Describe and use decision tree and tree-ensemble models -Describe and use other ensemble methods for classification -Use a variety of error metrics to compare and select the classification model that best suits your data -Use oversampling and undersampling as techniques to handle unbalanced classes in a data set   Who should take this course? This course targets aspiring data scientists interested in acquiring hands-on experience with Supervised Machine Learning Classification techniques in a business setting.   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 Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Probability, and Statistics....

Top reviews


Feb 21, 2022

Great course, well structured. The presentation of the different methods is very clear and well separated to understand the differences. A good understanding of classifiers is gained from this course.


Feb 28, 2021

Superb ,detailed, well explained, lots of hands on training through labs and most of the major alogrithms are covered!

Keep up the good work. You guys are helping the community a lot :D

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1 - 25 of 72 Reviews for Supervised Machine Learning: Classification

By Paul A

Feb 6, 2021

Overall, an excellent course. It gives a great introduction to many of modern and old machine learning models, and a brief glimpse in dealing with unbalanced data; a subject you can freely explore on your own. The strongest part of this course are the guided demos, they are excellent to see things happen in real time, with many ah-ha! moments, and filled code you can adapt to other projects.

However, there's a catch; to me, a big one. The guided demos; although excellent, are flawed. If you follow the practices presented in the demo, you generate a lot of data leakage into the predictions. Specially when doing cross validation with gridsearch, since the training is not done with a pipeline. Be careful when implementing your own machine learning models after following this course.

By Fitrie R

Dec 23, 2020

This course is a next level after understanding classification machine learning model. All my questions had been answered with this module. The instructor is very great to clarify the whole python code used. Highly recommended course

By Ashish P

Mar 1, 2021

Superb ,detailed, well explained, lots of hands on training through labs and most of the major alogrithms are covered!

Keep up the good work. You guys are helping the community a lot :D

By Abdillah F

Nov 8, 2020

Great course and very well structured. I'm really impressed with the instructor who give thorough walkthrough to the code.

By Volodymyr

Jul 28, 2021

Very good material and approach to Human Learning +5 :)

By Hossam G M

Aug 22, 2021

The course content is very great in the coding area and it is very helping. but a shortage that is clear is the theory behind every algorithm, the handling of it wasn't that much perfect.

By Mahitha P

May 28, 2022

Complex topics are not explained properly. The instructor just reads off the slides.


Aug 27, 2021

It is an excellent course on Classification. The approach of the course is different from similar courses I had attended earlier. It presents different classification algorithms as a continuous whole with increasing degree of sophistication rather as disjoint ones. This helped in understanding the entire range of available options and how to apply them in different situations. The faculty was very clear and precise in his presentations. Many thanks to IBM / Coursera.

By Amirarsalan G

Aug 20, 2023


- taught by the Elite

- state of the art

- diverse topics and learning material

- very clear and solid structure

- (partially) covering the mathematical background for each topic which deepens the roots of knowledge

- Python Labs with diverse coding examples and outlines

- a very logical connection to the courses which are predecessors (Data Exploration, Regression, ...)


- there could be more exercises directed at the learners' coding and conceptual abilities

By Willber d S N

Jan 25, 2023

One of the best data science courses on the platform. It has theory and a lot of practical content. Also, learn a number of classification models and how to deal with some of their problems. I recommend this course. I am very grateful to the teachers and the entire team that prepared this material of such high quality. Thank you very much.

By Shubham V

Apr 22, 2024

This Course gives me more informative techniques and tools that's used in this course. Coursera is the best platform that everyone can visit. And you can learn here Data analytics, Data scientists, Machine learning, Artificial Intelligence, and many other courses. Thank you Coursera, It is very interesting for me.

By Pulkit K

Oct 1, 2021

Excellent course . I have done a lot of data science courses on Coursera and this one by far is the most comprehensive course on this subject matter and the training examples in the notebook, all are very well explained. Highly recommend it to everyone.

By Nicola R

Feb 22, 2022

Great course, well structured. The presentation of the different methods is very clear and well separated to understand the differences. A good understanding of classifiers is gained from this course.

By Adolfo D

Feb 6, 2023

Well-structured learning path. If you dont have previous python experience you can catch up after a couple of weeks as the workflow is similar regardless of the algorithmn you are using

By Juan M

Jun 18, 2021

The course is very well structured, and the explanations very clear. I would only suggest enhancing the peer-review community since it takes a long time to get a review sometimes.

By Alparslan T

Jan 7, 2022

Excellent theoretical and practical understanding in classification algorithms. The instructor is really of a very high level and I appreciate his effort.

By Vallian S

Aug 8, 2022

It's a greate course. I learned a lot, from deeper understanding basic algorithms to more advanced technique such as bagging and model explanability.

By konutek

Dec 17, 2020

The instructor from videos is amazing. Great tutor. So far the courses from IBM Machine Learning Professional Certificate are really, really good.

By Jose M

Jan 19, 2021

I would like to give especial thanks to the instructor (the one in the videos) for his great job. It would be nice to know who is is.

By Rafael A O

Oct 29, 2022

A wonderful experience... learnt a lot and understood the rol of EDA, the method to evaluate classifiers with different metrics...

By nico l

Nov 26, 2021

Super content and good practice, perfect if you want to get an overview of all ML classification algo including ensemble methods !

By Saraswati P

Sep 23, 2021

Well structured training. Lab sessions and assignments are well planned to get clarity on concepts and practical application.


Sep 15, 2022

The course is well designed and easy to follow. (communication and feedback mechanism with Coursera could be improved).

By My B

Apr 19, 2021

A well-structured and practical course which helps me answer lots of my concerns from the past until now.

By Ranjith P

Apr 13, 2021

I recommend this course to everyone who wants to excel in Machine Learning. This is a Great Course!