<p>Lecture, four hours; discussion, two hours; outside study, six hours. Enforced requisite: course 32. Introduction of basic concepts, algorithms, and techniques of data mining on different types of datasets including vector data, set data, sequence data, text data, and graph data. Hands-on project involving practice of mining useful knowledge from large data sets. Letter grading.</p>

Computer Science

Henry Samueli School of Engineering and Applied Science

Container 1

COM SCI 145 - Introduction to Data Mining

Introduction to Data Mining

Gain initial experience in conducting research on data mining 

Develop skills to apply data mining algorithms to solve real-world applications 

Know what data mining is and learn the basic algorithms 

General Catalog

Introduction to Data Mining

COM SCI 145

4 units