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
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COURSE INTRODUCTION
Instructors
•Tutor: Dr. Hammad A. Qureshi
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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:
• Email: h.qureshi@mu.edu.sa
• Website:
• Counseling Hours: Every Monday or by appointment
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COURSE DETAILS
• 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.
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COURSE RESOURCES
• 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)
• www.cs.uiuc.edu/hanj/bk2
• www.mkp.com/datamining2e
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COURSE GRADING
• Grading Policy:
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20% Exam 1
20% Exam 2
40% Final Exam
10% Quizzes
10% Classwork & Assignments
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COURSE REQUIREMENT
• 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.
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STUDENT INTRODUCTION
• Please tell me about yourself
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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
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