Data mining Field of study: Computer Science
Programme code: 08-S2INIA15.2017

Module name: Data mining
Module code: 08-IN-ISI-S2-ED
Programme code: 08-S2INIA15.2017
Semester:
  • winter semester 2019/2020
  • winter semester 2018/2019
Language of instruction: English
Form of verification: course work
ECTS credits: 3
Description:
The purpose of this module is to prepare students to use various methods (algorithms) in data mining, used in practice, implemented in different systems (programs) supporting the process of knowledge discovery from data. This allows the student to demonstrate a full understanding of the subject matter of data mining, in particular he should know the role of data mining in the process of acquiring knowledge from the data. The result will be the ability to use the most important methods used in data mining. Student should be able to select the appropriate algorithms for a specific data analysis task. In order to be able to efficiently perform the data mining process, software is needed to support this process. As a result, the student should use the data mining programs without problems, with special attention paid to the programs distributed free of charge, 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]
Assessment of the student's knowledge of the content of lectures through the solution of the 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]
Preparation of project reports, describing the results obtained and sending them electronically within a specified time frame
 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.
 10
Familiarizing with topic of the lecture, taking advantage of: lectures electronic version, websites, recommended literature.
 20 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.
 20
Preparation for laboratory class Individual projects preparation, effecting reports on the realized projects and sending them on the fixed time.
40 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)