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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS BIL 3013 INTRODUCTION TO DATA MINING COMPULSORY 2 2 0 6

Offered By

Computer Science

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR EFENDI NASIBOĞLU

Offered to

Computer Science

Course Objective

Learning Outcomes of the Course Unit

1   Have a good understanding of data mining concepts 2   Have ability to identify the current system and describe data used in this system 3   Be capable to prepare data for the specific methods 4   Have a good understanding and interpretation of methods used in data mining 5   Evaluate, develope and deploy the project to real life

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to data mining, basic concepts 2 Data collection 3 Database, Data warehouses 4 Knowledge Discovery in Databases 5 Data understanding, Data visualization 6 Data preparation 7 Clustering methods, hierarchical clustering 8 k-means clustering, density based clustering 9 Classification methods, k-nearest neighbor algorithm 10 Decision trees, C4.5, CART 11 Neural Networks, fundamentals 12 Neural Networks - cont'd 13 Model evaluation 14 Data mining applications

Recomended or Required Reading

Textbook(s): - Han, J. , Kamber, M., Pei, J., Data Mining: Concepts and Techniques. 3rd Ed., Morgan Kaufmann Publishers, 2011 - Larose, Daniel T., Discovering Knowledge In Data An Introduction to Data Mining. New Jersey: John Wiley and Sons Ltd, 2005 Supplementary Book(s): - Tan, P., Steinbach, M., Kumar, V., Introduction to Data Mining, Addison Wesley, 2006 - Ilker Köse, Veri madenciliği: Teori, Uygulama ve Felsefesi. Papatya Yay. Eğitim, 2018.

Planned Learning Activities and Teaching Methods

Course is taught in a lecture, class presentation.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 ASG ASSIGNMENT 3 FIN FINAL EXAM 4 FCG FINAL COURSE GRADE MTE * 0.30 + ASG * 0.30 + FIN * 0.40 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + ASG * 0.30 + RST * 0.40 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

1 Midterm exam, Assignments and a Final exam.

Language of Instruction

Turkish

Course Policies and Rules

Students will come to the class in time. Attending the 70% of the classes are mandotary.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

Will be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 2 28 Tutorials 14 2 28 Preparations before/after weekly lectures 14 3 42 Preparation for midterm exam 1 10 10 Preparation for final exam 1 20 20 Preparing assignments 2 8 16 Final 1 2 2 Midterm 1 2 2 TOTAL WORKLOAD (hours) 148

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 PO.12 PO.13 LO.1 5 5 5 LO.2 5 5 5 LO.3 5 5 5 LO.4 5 5 5 LO.5 5 5 5