456-0921/01 – Data Analysis Methods (MAD)

Gurantor departmentDepartment of Computer ScienceCredits0
Subject guarantordoc. RNDr. Jana Šarmanová, CSc.Subject version guarantordoc. RNDr. Jana Šarmanová, CSc.
Study levelpostgraduateRequirementChoice-compulsory
YearSemesterwinter + summer
Study languageCzech
Year of introduction1997/1998Year of cancellation2010/2011
Intended for the facultiesHGF, FEIIntended for study typesDoctoral
Instruction secured by
LoginNameTuitorTeacher giving lectures
S1A65 doc. RNDr. Jana Šarmanová, CSc.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2
Part-time Credit and Examination 2+2

Subject aims expressed by acquired skills and competences

Graduate Course knows the basic theory, methods, types of data mining, can be practically applied to real data from structured databases, can analyze data from the sociological surveys, scientific experimental research, can analyze data from data warehouses.

Teaching methods

Lectures
Individual consultations
Project work

Summary

Evaluation and interpretation of information obtained from the measured and recorded data from the practice. Methods of data mining, mathematical, statistical and logical methods for solving this class of research and practical problems. Methods of searching for associations, clustering methods, classification methods and some other methods.

Compulsory literature:

Han, J., Kamber, M.: Data Mining: Concepts and Techniques. Second Edition. Elsevier Inc., 2006, 770 p., ISBN 1-55860-901-3.

Recommended literature:

Dunham, M.H.: Data Mining. Introductory and Advanced Topics. Pearson Education, Inc., 2003, 315 p.

Way of continuous check of knowledge in the course of semester

Continuous assessment: Treatment of the subject mining of the data. Terms of the credit: Meeting all three points of the follow-up studies, each at least 10 points.

E-learning

Other requirements

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

Lectures: Defining the problem of multivariate data analysis. Methods of data analysis: mathematical statistics and exploratory data analysis. The input data types of formal and semantic aspects. Filtration, missing data, dichotomize, categorization Preprocessing, transformation. Normalization and standardization. Principal components. Cluster analysis, non-hierarchical methods, hierarchical methods, presentation and interpretation of results. Finding associations, automatic creation of hypotheses, presentation and interpretation of results. Decision tree construction, presentation and interpretation. Exercise: Practice methods of lectures on examples of specific data. Papers on new methods of data mining. Reports on the results of an analysis. Projects: Analysis of specific data from their own experience or from a database. Preprocessing, selection of appropriate methods. Own calculations, interpretation. Presentation of results, documentation. Computer Labs: A system for data analysis, control methods, presentation of results, applications.

Conditions for subject completion

Full-time form (validity from: 1960/1961 Summer semester, validity until: 2012/2013 Summer semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Exercises evaluation and Examination Credit and Examination 100 (145) 51
        Examination Examination 100  0
        Exercises evaluation Credit 45  0
Mandatory attendence parzicipation:

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Occurrence in study plans

Academic yearProgrammeField of studySpec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2010/2011 (P3646) Geodesy and Cartography (3602V002) Geoinformatics P Czech Ostrava Optional study plan
2009/2010 (P2646) Information Technology (1801V002) Computer Science and Applied Mathematics K Czech Ostrava Choice-compulsory study plan
2009/2010 (P2646) Information Technology (1801V002) Computer Science and Applied Mathematics P Czech Ostrava Choice-compulsory study plan
2008/2009 (P2646) Information Technology (1801V002) Computer Science and Applied Mathematics P Czech Ostrava Choice-compulsory study plan
2008/2009 (P2646) Information Technology K Czech Ostrava Choice-compulsory study plan
2008/2009 (P2646) Information Technology (1801V002) Computer Science and Applied Mathematics K Czech Ostrava Choice-compulsory study plan
2007/2008 (P2646) Information Technology (1801V002) Computer Science and Applied Mathematics P Czech Ostrava Choice-compulsory study plan
2006/2007 (P2646) Information Technology (1801V002) Computer Science and Applied Mathematics P Czech Ostrava Choice-compulsory study plan
2005/2006 (P2646) Information Technology (1801V002) Computer Science and Applied Mathematics P Czech Ostrava Choice-compulsory study plan
2004/2005 (P2646) Information Technology (1801V002) Computer Science and Applied Mathematics P Czech Ostrava Choice-compulsory study plan
2003/2004 (P2646) Information Technology (1801V002) Computer Science and Applied Mathematics P Czech Ostrava Choice-compulsory study plan
2002/2003 (P2612) Electrical Engineering and Computer Science (1801V002) Computer Science and Applied Mathematics P Czech Ostrava Choice-compulsory study plan
2001/2002 (P2612) Electrical Engineering and Computer Science (1801V002) Computer Science and Applied Mathematics P Czech Ostrava Choice-compulsory study plan

Occurrence in special blocks

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