Utilisation of EU Employment Data in Lecturing Data Mining Course

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F21%3A73609750" target="_blank" >RIV/61989592:15310/21:73609750 - isvavai.cz</a>

Výsledek na webu

<a href="https://obd.upol.cz/id_publ/333189637" target="_blank" >https://obd.upol.cz/id_publ/333189637</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-77445-5_55" target="_blank" >10.1007/978-3-030-77445-5_55</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Utilisation of EU Employment Data in Lecturing Data Mining Course

Popis výsledku v původním jazyce

This article describes the utilisation of Eurostat employment data in the Data Mining course. The course is the obligatory course for a master degree Geoinformatics and Cartograhy study program at Palacký University in Olomouc. The article shows an example of the implementation of several methods like correlation, principal components analysis, k-means and hierarchical clustering on the same dataset in the course&apos;s teaching. The processing data in the Orange software and following interpretation of results gained by these methods are explained to students. Moreover, students create the MS PowerBI dashboard based on the same data. Teacher final finding is that the use of the current European data is for students more illustrative and increases their awareness of the status of employment in European countries within economic activities categorised by NACE. Practical processing of real data brings a deeper understanding of the lectured topics. Presented outputs, such as clustering, discover similar countries according to the same sector of employment.

Název v anglickém jazyce

Utilisation of EU Employment Data in Lecturing Data Mining Course

Popis výsledku anglicky

This article describes the utilisation of Eurostat employment data in the Data Mining course. The course is the obligatory course for a master degree Geoinformatics and Cartograhy study program at Palacký University in Olomouc. The article shows an example of the implementation of several methods like correlation, principal components analysis, k-means and hierarchical clustering on the same dataset in the course&apos;s teaching. The processing data in the Orange software and following interpretation of results gained by these methods are explained to students. Moreover, students create the MS PowerBI dashboard based on the same data. Teacher final finding is that the use of the current European data is for students more illustrative and increases their awareness of the status of employment in European countries within economic activities categorised by NACE. Practical processing of real data brings a deeper understanding of the lectured topics. Presented outputs, such as clustering, discover similar countries according to the same sector of employment.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10511 - Environmental sciences (social aspects to be 5.7)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Artificial Intelligence in Intelligent Systems

ISBN

978-3-030-77445-5

ISSN

2367-3370

e-ISSN

—

Počet stran výsledku

16

Strana od-do

601-616

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Zlin

Datum konání akce

1. 4. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—