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IŞIK UNIVERSITY FACULTY OF ARTS and SCIENCE IT433 Data Warehousing and Data Mining – Spring 2016 Level of Course: Undergraduate Language of English Instruction: Instructor: Gülay Ünel, [email protected], Office: AMF-220, Extension: 7188 Lectures: Tuesday 9AM – 12PM Grading Policy (Tentative) Quizzes and Participation Project Midterm Exam Final Exam %10 %30 %30 %30 A student must get at least 50 out of 100 from Participation to pass the course. Description Basic methods and techniques of data mining. Relationship between databases, data warehouses, and data mining. Data mining functionalities: association, concept description, classification, prediction and clustering. Various algorithms for each type of functionality such as decision tree classification, artificial neural networks, Bayesian classification, logistic regression, K-means clustering. Applications and trends in data mining. Project Each student will work on a project. The project will consist of 3 phases: I. proposal II. design, implementation & report III. presentation A student must attend the presentation to get a mark from the project report. Cheating Policy In case of any form of copying and cheating on assignments or exams, all involved parties will get 0 from the assignment/exam. Cheating has serious consequences such as suspension. Textbook You are responsible of the material that will be presented in the classroom. Textbook and the schedule references are for guidance only. Course Schedule (Tentative) Week 1 2 3 Date Feb. 14 Feb. 21 Feb. 28 Topics Course overview, Introduction Data Preprocessing Data Preprocessing (cont.) 4 March 7 5 March 14 6 March 21 7 March 28 8 9 10 Apr. 4 Apr. 11 Apr. 18 11 12 Apr. 25 May 2 13 May 9 14 May 16 Data Warehouse and OLAP Technology, Data Mining Tools Tutorial I Frequent Itemset Mining Methods Association Mining and Correlation Analysis Association Mining and Correlation Analysis (cont.) Association Mining and Correlation Analysis (cont.), Data Mining Tools Tutorial II Classification Classification (cont.) Prediction, Data Mining Tools Tutorial III Cluster Analysis Cluster Analysis (cont.), Data Mining Tools Tutorial IV Applications and Trends in Data Mining Project Presentation Notes Project phase I due Feb 28, Tuesday, 9AM Midterm on March 21 Tuesday 9AM – 11AM Project phase II due May 9, Tuesday, 9AM Project phase III