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Learner Reviews & Feedback for Unsupervised Machine Learning by IBM

245 ratings

About the Course

This course introduces you to one of the main types of Machine Learning: Unsupervised Learning. You will learn how to find insights from data sets that do not have a target or labeled variable. You will learn several clustering and dimension reduction algorithms for unsupervised learning as well as how to select the algorithm that best suits your data. The hands-on section of this course focuses on using best practices for unsupervised learning. By the end of this course you should be able to: Explain the kinds of problems suitable for Unsupervised Learning approaches Explain the curse of dimensionality, and how it makes clustering difficult with many features Describe and use common clustering and dimensionality-reduction algorithms Try clustering points where appropriate, compare the performance of per-cluster models Understand metrics relevant for characterizing clusters Who should take this course? This course targets aspiring data scientists interested in acquiring hands-on experience with Unsupervised Machine Learning 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


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Great course for learning about Unsupervised Learning


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

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1 - 25 of 42 Reviews for Unsupervised Machine Learning

By Tech S

Sep 2, 2021

No math , only superficial concepts. Not recommending to anyone else..

By az

May 10, 2022

Many typos and incorrect quizzes that haven't been fixed after several years.

By Hossam G M

Oct 4, 2021

This course is great from a coding and final project point of view. in this course I learned how to explore the different techniques and algorithms available to cluster unlabeled data. the notebook and videos are very great too. they walk you through the coding prospective step by step. but from the theory point of view, it is hard to well understand it well in these videos. you have to be aware of them first or study them on your own. although the quizzes aren't that much indicative about understanding. they need to be tougher and contain more questions. the last thing we should be provided the lecture sildes.

By Lea Z

Apr 18, 2021

As usual with IBM courses, the concepts are well explained and the split between theory and demo on python is very useful. However in this specific course there are a LOT of mistakes in graded tests, which have been spotted by users for months but are unanswered by course owners in discussion forums. It is a shame, and hopefully the last two modules of the professional certification are benefitting from a better maintenance.

By Anish D

Apr 19, 2021

It is a beautifully crafted course that looks at various clustering algorithms. More importantly, show the pros and cons of each algorithm/technique based on different patterns.

By Abdillah F

Nov 7, 2020

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

By Ashish P

Mar 13, 2021

Very Well Structured, concepts clearly explained, lots of Labs to get a hands-on practice and in the end a summary of all the key points explained.

A couple of Labs for DBSCAN and Mean-Shift would have been great.

The concept of SVD with the matrices was not very clear from the videos. Maybe some detailed notes on how the matrices are divided into the submatrices could be really helpful.

By Dan M

Jul 21, 2023

This was a very useful overview of two types of unsupervised learning - clustering and decomposition. I had a passing familiarity with some of these techniques, but this course introduced me to a wider array of techniques I had not heard of, along with the underlying theory and comparison between models.

By Sid C

Apr 5, 2022

This course enabled me to further develop my standard work process in performing Machine Learning activities. It also expanded my existing skills set with the addition of Unsupervised Machine Learning methods --this actually significantly improved my model performances.


Sep 20, 2021

I found the learning experience extremely good and absorbing. The approach of the program to impart theoritical background of algorithms before taking of Labs is very helpful. Also, after the course one gets a broad view of the contexts behind different approaches.

By Alparslan T

Oct 30, 2022

Excellent course on unsupervised ML. Clustering, dimensionality reduction and even classification are very well explained and practiced with high level coding on Python. Thanks IBM.

By V. A

Jul 6, 2021

Great course. Maybe there is one instance of wrong answer in one of the quizzes. Everything elese is perfect. Thanks IBM !

By Gabriel C S

Apr 16, 2024

Great mix of theory and application, not too superficial and not too deep. Amazing experience!

By Tim T

Feb 21, 2023

Excellent course for me! I had a lot of "Ah ha!" moments during the course! Phenomenal!

By Ndowah M A

Jun 22, 2024

Exceptional content. Thank you so much for taking time to create this for us.


May 22, 2021

Sometimes so fast, but it motives to research more and more about ML.

By george s

Sep 3, 2021

Excellent course! Just examples of clustering could be a bit better.

By Marwan K

Feb 22, 2022

Thank you Coursera.

Thank you IBM.

Thank you to all instructors.

By Luis P S

Jun 2, 2021

Excellent!! Easy and good way to learn unsupervised algorithms!

By My B

Apr 23, 2021

A high quality course with lots of practical techniques

By Nikolas R W

Dec 26, 2020

Great course for learning about Unsupervised Learning

By Krishnendu D

Apr 11, 2022

Awesome and wholesome explaination of the concepts

By Jose M

Jan 25, 2021

Again, congrats to the instructor on the videos.

By Saraswati P

Oct 23, 2021

Well structured course with many examples

By Veronica A T S

Jun 27, 2021

i wouuld have liked a notebook on dbscan