<p> Rzeszów University of Technology</p><p>The Faculty of: Electrical and Computer Engineering</p><p>Field of study: Computer Science</p><p>Speciality:</p><p>Study degree (BSc, MSc): MSc</p><p>COURSE UNIT DESCRIPTION</p><p>Course title: Knowledge Discovery and Data Mining </p><p>Lecturer responsible for course: dr inż. Krzysztof Świder</p><p>Contacts: phone: +17 865 1548 e-mail: [email protected]</p><p>Department: Computer Science and Automatic Control</p><p>Type of classes Number of Semester Weekly load C ECTS L Lb P Theoretical credits Lectures Laboratory Project Classes 1 10/3 30 20 4</p><p>Course description</p><p>Lecture: Emergence and evolution of knowledge discovery systems. The general schema of knowledge discovery and the data mining phase. The comparison of existing data analysis methods: i) query and reports, ii) online analytical processing and iii) data mining. Data warehouses and data marts. Data warehouse design and the star schema. The key features and operations of OLAP applications. An overview of common data mining techniques (decition tree models, clusters and association rules). The formal definition of association rules, rule interestingness and association analysis. The problem of association rule mining and employment of Apriori algorithm to find frequent itemsets. Data preprocessing for analysis - the motivation and typical methods (cleaning, integration, transformation and reduction).</p><p>Laboratory: Multidimensional analysis (OLAP) of the real data in MS SQL Server environment. Building classification models and mining clusters and association rules with Oracle and Matlab tools. Mining multidimensional association rules from Web data.</p><p>Objectives of the course</p><p>Learning advanced methods and techniques for knowledge discovery from data. Achieving the practical skills in using multidimensional analysis and data mining tools to analyse exemplary data. Examination method</p><p>The positive result of written test.</p><p>Bibliography</p><p>1. Larose D. T.: Odkrywanie wiedzy z danych Wprowadzenie do eksploracji danych. PWN, 2006. 2. Hand D., Mannila H., Smyth P.: Eksploracja danych. WNT 2005.</p><p>3. Han J., Kamber M.: Data Mining. Concepts and Techniques. Second Edition. Morgan Kaufmann 2006. 4. Zgłębianie i analiza danych w Microsoft SQL Server 2000. Przewodnik techniczny. APN PROMISE, 2002.</p><p>Lecturer signature</p><p>Head of Department signature</p><p>Dean signature</p>