Course title |
Artificial Intelligence in Mobile Systems |
Acronym |
19M034VIM |
Study programme |
Electrical Engineering and Computing |
Module |
Applied Mathematics, Audio and Video Technologies, Biomedical and Environmental Engineering, Biomedical and Nuclear Engineering, Computer Engineering and Informatics, Electronics and Digital Systems, Energy Efficiency, Information and Communication Technologies, Microwave Engineering, Nanoelectronics and Photonics, Power Systems - Networks and Systems, Power Systems - Renewable Energy Sources, Power Systems - Substations and Power Equipment, Signals and Systems, Software Engineering |
Type of study |
master academic studies |
Lecturer (for classes) |
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Lecturer/Associate (for practice) |
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Lecturer/Associate (for OTC) |
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ESPB |
6.0 |
Status |
elective |
Condition |
Radio Systems |
The goal |
Mobile networks are part of our everyday lives, whereas the use of AI is growing rapidly. The goal of this course is to provide students with an introduction to problems and techniques of AI. In a step-by-step manner, the following AI techniques are introduced: supervised , unsupervised and reinforcement learning. It explains how these techniques can be used for future wireless networks. |
The outcome |
Student who completes this course is expected to:
* understands the basic concepts of various techniques of artificial intelligence,
* understands the possibility of applying machine learning in different segments of a mobile network,
* master the basic algorithms and software tools for applying the techniques of machine learning to specific problems. |
- Haesik Kim, Artificial Intelligence for 6G, Springer International Publishing, 2022 (Original title)
- Yuanming Shi, Kai Yang, Zhanpeng Yang, Yong Zhou, Mobile Edge Artificial Intelligence Opportunities and Challenges, Elsevier, 2021. (Original title)
- Ian Goodfellow, Yoshua Bengio, Aaron Courville, Deep Learning, MIT Press, 2016.god (Original title)
- Hassoun M., Fundamentals of Artificial Neural Networks. Massachusetts MA: The MIT Press; 2003. (Original title)
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