Pattern Discovery in Data Mining

Module 1 provides an introduction to the course, allowing you to familiarize yourself with the syllabus, discussion forums, and social media. You will also engage in an orientation quiz and interact with your classmates to create a collaborative learning environment.

Module 2 delves into the fundamental concepts of pattern discovery, covering frequent patterns, association rules, compressed patterns, and the Apriori algorithm. You will also learn about different mining approaches and engage in quizzes to reinforce your knowledge.

Module 3 explores interestingness measures, limitations of the support-confidence framework, and various association mining techniques. You will gain insights into multi-level associations, multi-dimensional associations, and quantitative associations through engaging lessons and quizzes.

Module 4 focuses on sequential pattern mining, spatial associations, and mining diverse movement patterns. You will explore methods for mining sequential patterns, spatial colocation patterns, and semantics-rich movement patterns in this comprehensive module.

Module 5 delves into phrase mining methods and explores diverse applications of pattern discovery in data mining, such as data stream mining, software bug mining, image analysis, and advanced topics related to pattern mining and society. This module provides a holistic understanding of pattern discovery applications.