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.
Unsupervised Machine Learning
Give your career the gift of Coursera Plus with $160 off, billed annually. Save today.
Unsupervised Machine Learning
This course is part of multiple programs.
Instructors: Mark J Grover
28,766 already enrolled
Included with
Gain insight into a topic and learn the fundamentals.
4.7
(266 reviews)
Intermediate level
Some related experience required
Flexible schedule
Approx. 23 hours
Learn at your own pace
94%
Most learners liked this course
Skills you'll gain
Details to know
Earn a career certificate
Add to your LinkedIn profile
Assessments
14 assignments
Taught in English
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
This course is available as part of
When you enroll in this course, you'll also be asked to select a specific program.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
There are 7 modules in this course
This module introduces Unsupervised Learning and its applications. One of the most common uses of Unsupervised Learning is clustering observations using k-means. In this module, you become familiar with the theory behind this algorithm, and put it in practice in a demonstration.
What's included
11 videos2 readings3 assignments3 app items
What's included
6 videos1 reading2 assignments2 app items
In this module, you become familiar with some of the computational hurdles around clustering algorithms, and how different clustering implementations try to overcome them. After a brief recapitulation of common clustering algorithms, you will learn how to compare them and select the clustering technique that best suits your data.
What's included
11 videos1 reading3 assignments3 app items
This module introduces dimensionality reduction and Principal Component Analysis, which are powerful techniques for big data, imaging, and pre-processing data.
What's included
5 videos1 reading2 assignments4 app items
This module introduces dimensionality reduction techniques like Kernal Principal Component Analysis and multidimensional scaling. These methods are more powerful than Principal Component Analysis in many applications.
What's included
2 videos1 reading2 assignments3 app items
This module introduces matrix factorization, which is a powerful technique for big data, text mining, and pre-processing data.
What's included
3 videos1 reading2 assignments3 app items
Now, you have all the tools in your toolkit to highlight your Unsupervised Learning abilities in your final project.
What's included
1 peer review
Instructors
Instructor ratings
4.6 (73 ratings)Offered by
Recommended if you're interested in Machine Learning
DeepLearning.AI
Fractal Analytics
Alberta Machine Intelligence Institute
University of Pennsylvania
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Learner reviews
Showing 3 of 266
4.7
266 reviews
- 5 stars
77.44%
- 4 stars
16.54%
- 3 stars
2.63%
- 2 stars
1.50%
- 1 star
1.87%
New to Machine Learning? Start here.
Open new doors with Coursera Plus
Unlimited access to 7,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.