Data Mining Field of study: Computer Science
Programme code: 08-S2INIA15.2016

Module name: Data Mining
Module code: 08-IN-ISI-S2-ED
Programme code: 08-S2INIA15.2016
Semester: winter semester 2017/2018
Language of instruction: English
Form of verification: course work
ECTS credits: 3
Description:
The aim of classes in this module is preparing the students to use various methods (algorithms) in data mining, used in practice, implemented in various systems (programs) supporting the process of discovering knowledge from data. Thank to this class, the student should exhibit full understanding of issues connected with data mining, especially should know the role of data mining in the process of discovering knowledge from data. The result will be ability to use the most important `used in data mining. The student should be able to choose appropriate algorithms for the specific data analysis task. To perform the process of data mining efficiently, necessary is software which supports the process. Therefore, the student should seamlessly use programs used in data mining, especially these, which are disseminated free of charge, among others RapidMiner, RSES and Weka.
Prerequisites:
(no information given)
Key reading:
(no information given)
Learning outcome of the module Codes of the learning outcomes of the programme to which the learning outcome of the module is related [level of competence: scale 1-5]
Is able to formulate opinions on various issues concerning current state and developmental trends in analysis and data mining. [ED _K_10]
 K_2_A_I_K01 [3/5] K_2_A_I_K06 [2/5]
Can work on various tasks and realize them on time; knows how to co-operate in several persons team, undertaking different roles. [ED _K_9]
 K_2_A_I_K03 [3/5]
Can acquire information from literature, data bases and other appropriately chosen sources, also in English in the field of data mining; can integrate obtained information, perform critical analysis and evaluation and also, draw conclusions and formulate opinions. [ED _U_5]
 K_2_A_I_U01 [3/5] K_2_A_I_U18 [2/5]
Is able to identify and formulate specification of tasks from the field of data mining; can differentiate main stages in discovering knowledge from data. [ED _U_6]
 K_2_A_I_U18 [5/5]
Can choose appropriate methods of data mining and choose algorithms solving the given problem. Is able to evaluate the obtained results (patterns). [ED _U_7]
 K_2_A_I_U03 [1/5] K_2_A_I_U18 [5/5] K_2_A_I_U22 [1/5]
Is able to take advantage of available programs in order to perform analysis process. [ED _U_8]
 K_2_A_I_U02 [1/5] K_2_A_I_U18 [5/5]
Has knowledge from the field of basic notion of data mining and discovering knowledge from data. [ED_W_1]
 K_2_A_I_W17 [5/5]
Knows main methods of data mining including: discovering association, classification (prediction), grouping, singular points discovering. Knows fields of various data mining methods usage. [ED _W_2]
 K_2_A_I_W03 [1/5] K_2_A_I_W09 [1/5] K_2_A_I_W17 [5/5]
Knows software used in data mining. [ED _W_3]
 K_2_A_I_W09 [1/5] K_2_A_I_W17 [5/5]
Possesses knowledge of developmental trends and most important new achievements in the field of discovering knowledge from data. [ED _W_4]
 K_2_A_I_W14 [2/5] K_2_A_I_W17 [5/5]
Type Description Codes of the learning outcomes of the module to which assessment is related
Written test in lecture knowledge [ED _w_1]
Evaluation of the student’s knowledge in lecture knowledge by a test
 ED_W_1 ED _W_2 ED _W_3 ED _W_4
Preparing projects/programs [ED _w_2]
Preparing a project/program in a group of 1-3 students, which realizes the process of discovering knowledge from data, taking advantage of available programs.
 ED _K_10 ED _K_9 ED _U_5 ED _U_6 ED _U_7 ED _U_8 ED_W_1 ED _W_2 ED _W_3 ED _W_4
Reports [ED _w_3]
Preparing project reports, with description of the results obtained and sending electronic copy in a fixed date.
 ED _K_10 ED _K_9 ED _U_5 ED _U_6 ED _U_7 ED_W_1 ED _W_2 ED _W_3
Form of teaching Student's own work Assessment of the learning outcomes
Type Description (including teaching methods) Number of hours Description Number of hours
lecture [ED _fs_1]
Giving educational content orally, with use of content visualization. Drawing attention to material conceptually complex and indicating additional material.
 15
Familiarizing with topic of the lecture, taking advantage of: lectures electronic version, websites, recommended literature.
 15 Written test in lecture knowledge [ED _w_1]
laboratory classes [ED _fs_2]
Designed for students’ detailed preparation to realize assigned projects indicating methodology of proceedings, pointing the sequence of performed activities.
 30
Preparation for laboratory class Individual projects preparation, effecting reports on the realized projects and sending them on the fixed time.
30 Preparing projects/programs [ED _w_2] Reports [ED _w_3]
Attachments
Module description (PDF)
Information concerning module syllabuses might be changed during studies.
Syllabuses (USOSweb)
Semester Module Language of instruction
(no information given)