DATA MINING: LECTURE 1 By Dr. Hammad A. Qureshi Introduction to the Course and the Field There is an inherent meaning in everything. “Signs for people.

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Presentation transcript:

DATA MINING: LECTURE 1 By Dr. Hammad A. Qureshi Introduction to the Course and the Field There is an inherent meaning in everything. “Signs for people who can see.”

AGENDA Course Introduction Course Details Student Introduction 2

C OURSE I NTRODUCTION Instructors Tutor: Dr. Hammad A. Qureshi PhD Computer Science, University of Warwick UK Majors in Data Mining and Pattern Recognition 10 years commercial work experience in software development Location: Office inside the Distributed Systems Lab Contacts Telephone: Website: Counseling Hours: Every Monday or by appointment 3

C OURSE D ETAILS Course Description: The course of Data Mining teaches the students Basic principles, techniques, tools and applications of Data Mining. Science of data mining as the automatic extraction of patterns representing knowledge stored in large databases, data warehouses, and other massive information repositories About the overlap that exists with areas such as machine learning and pattern recognition. The concepts of data pre-processing, cluster analysis, classification and prediction, frequent pattern mining and data warehousing. 4

C OURSE R ESOURCES Text book: Data Mining: Concepts and Techniques (3rd Edition) by Jiawei Han, Micheline Kamber and Jian Pei Reference book: Elements of Statistical Learning by Hastie, Tibshirani and Friedman Freely available online (google for it) Website: Some useful resources may be found at Jiawei Han’s website (the lectures are inspired from him) 5

C OURSE G RADING Grading Policy: 20% Exam 1 20% Exam 2 40% Final Exam 10% Quizzes 10% Classwork & Assignments 6

C OURSE R EQUIREMENT You should have some knowledge of the concepts and terminology associated with database systems, statistics, machine learning. You should have some programming experience. In particular, you should be able to read pseudo-code and understand simple data structures such as multidimensional arrays. 7

S TUDENT I NTRODUCTION Please tell me about yourself What is your name and where are you from? What are your interests? Which is your favourite computer science course? Have you studied a similar course to Data Mining before? What do you think should be the content of the course? Programming? How many of you know how to write programs? How would you rate yourself in programming (scale 1-10)? Excellent 8-10, Good, 6-8, Average 4-5, Bad 1-3 8