Nov 22, 2019   9:16 p.m.      Cecília        
University information system

Course syllabus MIAX10005 - Big Data, Data Mining (FI - SS 2019/2020)


     Information sheet          


     Slovak          English          


University: Pan-european University
Faculty: Faculty of Informatics
Course unit code: MIAX10005
Course unit title: Big Data, Data Mining
Planned learning activities and teaching methods:
workshop2 hours weekly / 24 hours per semester of study (on-site method)

Credits allocated: 6
Recommended semester/trimester: 2.
 
Level of study: 2.
Prerequisites for registration: none
 
Assessment methods:
Students must obtain at least 20 points from total of 40 points(control tests, homework) during the semester to be allowed to take an exam. Student can obtain 60 points for the exam. The grade A is obtained for 94-100 points, B for 86-93 points, C for 76-85 points, D for 66-75 points, E for 56-65 points and FX for 0-55 points.
 
Learning outcomes of the course unit:
The goal of the course is to educate the students about basic and andvanced techniques of effective implementation and storage of large amount of data. To demonstrate analysis and report creation in most used available Hadoop technologies(HBase, Hive, ...). To acquaint the students with predictive and statistical analysis, data mining. To demonstrate applications of Big Data principles in healthcare and in social networks.
 
Course contents:
1. Introduction to interaction with large amount of data and data mining
2. Aggregations of large amount of data from different sources inside and outside an organization
3. New knowledge based on collected available data. Customer behaviour recognition
4. Usage of collected data for improving work productivity in bussiness environment
5. Web intelligence
6. Predictive analysis
7. Statistical analysis
8. Text mining mechanisms
9. Data mining mechanisms
10. Big Data in healthcare
11. Social network analysis
 
Recommended or required reading:
Basic:
LACKO, L. Datové sklady, analýza OLAP a dolování dat s příklady SQL Servera Oracle. Brno: Computer Press, 2003. ISBN 80-7226-969-0.
LABERGE, R. Datové sklady. Agilní metody a business intelligence. Brno: Computer Press, 2012.
WARDEN, P. Big Data Glossary. USA: O'Reilly Media, 2011.
RUSSELL, M. Mining the Social Web. Second edition. USA: O'Reilly Media, 2013.

 
Language of instruction: Slovak, English
 
Notes:
 
Courses evaluation:
Assessed students in total: 120

ABCDEFX
24,2 %20,8 %21,7 %18,3 %14,2 %0,8 %
 
Name of lecturer(s): Ing. Ján Doboš (examiner, instructor, lecturer)
Ing. Július Hlaváč, PhD. (person responsible for course)
Last modification: 11. 6. 2019
Supervisor: Ing. Július Hlaváč, PhD.


Last modification made by Ján Lukáš on 06/11/2019.

Type of output: