Extending Networking Curriculum with Applied Artificial Intelligence
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F19%3APU134165" target="_blank" >RIV/00216305:26230/19:PU134165 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9000455" target="_blank" >https://ieeexplore.ieee.org/document/9000455</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/EAEEIE46886.2019.9000455" target="_blank" >10.1109/EAEEIE46886.2019.9000455</a>
Alternative languages
Result language
angličtina
Original language name
Extending Networking Curriculum with Applied Artificial Intelligence
Original language description
Artificial Intelligence (AI) and related technologies like data mining, machine learning or neural networks became very popular in recent years. Many IT companies today require graduated students to understand and be able to apply these technologies. Application potential of AI is not limited only to robotics, image processing or intelligent agents but also in engineering areas like computer networking and communication. However, on most universities, networking courses focus mainly on transmission protocols, network services and hardware design only while AI, machine learning or neural networks are taught separately. This causes a gap that emerges between AI theory and engineering approach. Thus, teachers of engineering courses are challenged how to introduce their students to an application of AI in the engineering areas, e.g., electronics, communication, embedded systems, power grids, etc. This paper shows how selected AI techniques presently used in computer networks can be incorporated into networking curriculum and demonstrated to students which extends student competencies and prepares them better into future jobs. We also present two case studies where AI techniques are applied on networking data in order to solve typical engineering problems.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20206 - Computer hardware and architecture
Result continuities
Project
<a href="/en/project/TF03000029" target="_blank" >TF03000029: Internet of Things Monitoring and Forensics (IRONSTONE)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of EAEEIE 2019
ISBN
978-1-7281-3222-8
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
11-16
Publisher name
Institute of Electrical and Electronics Engineers
Place of publication
Ruse
Event location
Ruse
Event date
Sep 4, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000719758500043