Advanced methods of data analysis Field of study: Computer Science
Programme code: W4-S2IN19.2020

Module name: Advanced methods of data analysis
Module code: W4-IN-S2-20-F-ZMAD
Programme code: W4-S2IN19.2020
Semester:
  • summer semester 2021/2022
  • winter semester 2021/2022
  • summer semester 2020/2021
Language of instruction: Polish
Form of verification: course work
ECTS credits: 4
Description:
The lectures will discuss the recognition of phenomena occurring in data sets. These phenomena, such as Boolean function properties, data compression or steganography, will be detected using selected discrete transforms like Fourier, Cosine, Sine as well as Walsh or Haar.
Prerequisites:
(no information given)
Key reading:
R. Wang Introduction to Orthogonal Transforms with Applications in Data Processing and Analysis. Cambridge University Press. 2012. N. Ahmed, K.R. Rao Orthogonal Transforms for Digital Signal Processing. Springer Verlag, 1975. P. Porwik Wybrane metody cyfrowego przetwarzania sygnałów z przykładami programów w Matlabie. Wyd. Uniwersytetu Śląskiego, 2015.
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]
The aim of the module is to present the possibilities of data analysis using various methods based on signal theory using spectral methods of analysis. Data analysis aims to extract useful information from data and make decisions based on data distribution. The acquired skills will help students in cleaning, transforming and modeling data in finding useful information for business, as well as in making scientific decisions. [M_001]
 K_W01 [1/5] K_W09 [1/5] K_U01 [1/5] K_U02 [1/5] K_U03 [1/5] K_U05 [1/5] K_U09 [1/5] K_K04 [1/5] K_K05 [1/5]
Type Description Codes of the learning outcomes of the module to which assessment is related
test [W_001]
The purpose of the test is to verify learning progress and suggestions for necessary repetitions of the material along with participation in consultations
 M_001
Preparation of a computer program [W_002]
The student presents and discusses the implementation details of the program which solves the problem of analyzing data given in the form of a set of numbers.
 M_001
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 [Z_001]
Lectures will be supported by audiovisual methods. The theoretical foundations of selected data analysis methods will be discussed along with examples of practical applications. Some lectures also include discussion with students about possible solution options.
 15
The student should read the relevant literature materials for each lecture. To better understand the problem, the student should also solve the examples given in the lectures and consult them with the lecturer.
 45 test [W_001]
laboratory classes [Z_002]
Matlab will be introduced as a programming method in the laboratory. The student develops computer programs that can be used to solve tasks discussed in lectures or tasks indicated by the laboratory teacher. Program issues will be discussed during laboratory meetings.
 30
During individual work the student should check different versions of the program code, paying attention to program optimization. Different discrete transformations can be programmed in different ways, generating different approximations of results, these nuances should be checked during their own work.
 30 test [W_001] Preparation of a computer program [W_002]
Attachments
Module description (PDF)
Information concerning module syllabuses might be changed during studies.
Syllabuses (USOSweb)
Semester Module Language of instruction
(no information given)