LECTURE 1. INTRODUCTION TO AI AND KNOWLEDGE DISCOVERY

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LECTURE 1. INTRODUCTION TO AI AND KNOWLEDGE DISCOVERY

INSTRUCTOR: DR. AMR ABDULLAH MUNSHI

SELECTED-TOPICS: KNOWLEDGE DISCOVERY AND DATA MINING

INSTRUCTOR

Dr. Amr Abdullah Munshi

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Office: 1^stfloor, room 1083

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Email: [email protected]

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Office hours: by appointment or fixed date

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BASICS

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Lectures: Mondays 18:00-18:50 and 20:00-21:40

DR. AMR MUNSHI, 2019 3

PREREQUISITES

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14012402-4 Algorithms

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4042301-3 Statistics

TEXTBOOKS

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Cios KJ, Pedrycz W, Swiniarski RW, and Kurgan L, Data Mining: A Knowledge Discovery Approach, ISBN: 978-0-387-33333-5, Springer, 2007.

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Han J, Kamber M, and Pri J, Data Mining Concepts and Techniques, 3^rdEdition, ISBN: 978-12-381479-1, Elsevier, 2012.

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Class notes will be provided by the instructor.

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ATTENDANCE POLICY

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Students are expected to attend every class, to arrive on time, and to

participate in all class activities. Missing class more than 25% with or without a legitimate excuse will result in withdrawal from the course. If you must miss class for any reason you are responsible for any work that you miss, and missing class is no excuse for not turning in an assignment.

LATE SUBMISSION POLICY

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All submissions must be turned in on the due date. Late submissions turned in within 24 hours from the due date will receive a 50% penalty. Submissions will not be accepted more than 24 hours late.

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RECORDING OF LECTURES

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Recording is permitted only with the prior written consent of the instructor. If a lecture is to be recorded, the instructor must notify the class that this is taking place and the person making the recording may need to obtain the permission of all other individuals that appear in the recording.

ACADEMIC INTEGRITY

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Umm Al-Qura University is committed to the highest standards of academic integrity and honesty. Students are expected to be familiar with these standards regarding academic honesty and to uphold the policies of the University in this respect. Students are urged to familiarize themselves with the provisions of the Student Responsibilites (online at

https://uqu.edu.sa/studaff/App/FILES/11155), and avoid any behaviour which could potentially result in suspicions of cheating, plagiarism,

misrepresentation of facts and/or participation in an offence.

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COURSE EVALUATION

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Attendance (5%)

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Assignments ~4-5 (20%)

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Project + Presentation (20%)

Presentation: marked by your peers (50% of the mark; done by project groups) and the instructor (50% of the mark)

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Midterm (15%)

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Final Exam (40%)

TOPICS COVERED

• Lec1: Introduction

• Lec2: An introduction to Artificial Intelligence and Knowledge Discovery

• Lec3: Data

• Lec4: Database Management Systems and SQL

• Lec5: Problem Solving by Searching

• Lec6: Knowledge Discovery Process

• Lec7: Learning from Data

• Lec8: Supervised Learning – Machine Learning

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NOTES

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No calculators or any other electronic devices are allowed at the exam.

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NO MAKEUP EXAMS.

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Instructor reserves the right to change the course outline and the deadlines based on students' progress and coverage of the material.