Cluster Analysis in Data Mining

This course is part of Data Mining Specialization

Instructor: Jiawei Han

Skills you'll gain

  •   Exploratory Data Analysis
  •   Algorithms
  •   Data Mining
  •   Data Validation
  •   Statistical Methods
  •   Machine Learning Algorithms
  •   Unsupervised Learning
  •   Applied Machine Learning
  •   Data Analysis

    • There are 6 modules in this course

    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.

    Module 1

    Week 2

    Week 3

    Week 4

    Course Conclusion

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