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Week
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Topics
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Study Metarials
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1
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Introduction to Data Mining
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R2 - Chapter 1
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2
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Data Mining Concepts and Data Preprocessing Techniques
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R1 - Chapter 2-3
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3
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Data Reduction and Data Discretization-I
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R1 - Chapter 3
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4
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Data Reduction and Data Discretization-II
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R1 - Chapter 3
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5
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Decision Trees and Decision Rules
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R1 - Chapter 7
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6
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Statistical Classification Methods, Naïve Bayesian Classification
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R1 - Chapter 5
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7
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Evaluation Methods on classification, Class confusion Matrix
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R1 - Chapter 4
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8
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Clustering Methods: K-Means Alg. And Hierarchical Clustering
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R1 - Chapter 6
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9
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Association Rules, Market Basket Analysis, Apriori Algorithm
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R1 - Chapter 8
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10
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Data Warehouse and OLAP Technologies, OLAP Operations in the Multidimensional Data Models
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R2 - Chapter 10
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11
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Web Mining
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R2 - Chapter 11
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12
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Classification with Artificial Neural Networks
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R1 - Chapter 9
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13
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Project presentation - I
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Project presentation
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14
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Project presentation - II
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Project presentation
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Prerequisites
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-
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Language of Instruction
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Turkish
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Responsible
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Asist. Prof. Dr. Selim BUYRUKOĞLU
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Instructors
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1-)Doçent Dr Selim Buyrukoğlu
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Assistants
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Research Assistant Selim SÜRÜCÜ
Research Assistant Esra SİVARİ
Research Assistant İrem Nur ECEMİŞ
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Resources
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R1. Kantardzic, M. (2019). Data Mining: Concepts, models, methods, and algorithms. (3rd Edition). Wiley-IEEE Press.
R2.Han, J., Kamber, M. & Kaufman, M. (2001). Data Mining. Academic Press.
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Supplementary Book
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SR1. Pektaş, A. O., (2013). SPSS ile veri madenciliği. Dikeyeksen Yayıncılık, İstanbul.
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Goals
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Introducing the basic concepts and techniques of Data Mining. Develop skills in using data mining techniques to solve practical problems. To gain the ability to apply text analysis techniques. Gaining experience of working independently and doing research.
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Content
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Introduction to Data Mining, Data Mining Concepts and Data Preprocessing Techniques, Data Reduction and Data Discretization, Decision Trees and Decision Rules, Web Mining, Classification with Artificial Neural Networks
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Program Learning Outcomes |
Level of Contribution |
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1
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Acquires information by carrying out scientific research in the field of Electronics and Computer Engineering, evaluates the findings and makes comments
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3
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2
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Complements the restricted or incomplete information and applies it, unifies the multidisciplinary information
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-
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3
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Designs and implements a system meeting the requirements in the field of Electronics and Computer Engineering
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-
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4
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Makes an interpretation of a problem in the field of Electronics and Computer Engineering, develops models for solutions and applies innovative methods in these solutions
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-
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5
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Has comprehensive knowledge on the contemporary applied method and techniques used in the field of Electronics and Computer Engineering and their limitations
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4
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6
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Undertakes and implements analytic, simulation or experimental types of research and has the ability to solve the complex problems encountered there
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-
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7
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Can participate and assume responsibility in multidisciplinary task forces
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4
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8
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Observes the scientific, professional and ethical rules during data collection, its introduction and interpretation
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4
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9
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Be aware of recent advances and developments in the field of Electronics and Computer Engineering learns, analyses and applies them wherever needed
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-
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10
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Publishes his/her research findings verbally and in written forms in the national and international arena
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-
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