Discover the basic concepts of cluster analysis, and then study a set of typical clustering methodologies, algorithms, and applications. This includes partitioning methods such as k-means, hierarchical methods such as BIRCH, and density-based methods such as DBSCAN/OPTICS. Moreover, learn methods for clustering validation and evaluation of clustering quality. Finally, see examples of cluster analysis in applications.
About this Course
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessSkills you will gain
- Cluster Analysis
- Data Clustering Algorithms
- K-Means Clustering
- Hierarchical Clustering
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessGet a head start on your degree
Syllabus - What you will learn from this course
Course Orientation
Module 1
Week 2
Week 3
Week 4
Course Conclusion
Reviews
- 5 stars66.25%
- 4 stars23.25%
- 3 stars5.75%
- 2 stars2.25%
- 1 star2.50%
TOP REVIEWS FROM CLUSTER ANALYSIS IN DATA MINING
This was my favorite course in the whole specialization. Everything is explained very concisely and clearly making the subject matter very easy to understand.
Good course for understanding the Cluster Analysis & Algorithms, instructor is very experienced and well explained, thanks
A very good course, it gives me a general idea of how clustering algorithm work.
Very informative lectures, wonderful assignments. This course isn't so easy but it gives you real knowledge and useful experience.
About the Data Mining Specialization
Frequently Asked Questions
When will I have access to the lectures and assignments?
What will I get if I subscribe to this Specialization?
Is financial aid available?
More questions? Visit the Learner Help Center.