AGH University of Krakow, Poland (Previous name: AGH University of Science and Technology)
Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering
Department of Biocybernetics and Biomedical Engineering
Field of Biocybernetics, Cognitivistics and Artificial Intelligence
is already under construction and will be available at the spring semester in 2017/2018.
This course will include 14 lectures and 14 laboratory classes.
What is this course about?
This course is intended to give students a broad overview and deep knowledge about popular solutions and efficient neural network models as well as to learn how to construct and train intelligent learning systems in order to use them in everyday life and work. During the course we will deal with the popular and most efficient models and methods of neural networks that enable us to find specific highly generalizing models solving difficult tasks. We will also tackle with various CI and AI problems and work with various data and try to model their structures in such a way to optimize operations on them throughout making data available without necessity to search for them. This is a unique feature of associative structures and systems. These models and methods will allow us to form and represent knowledge in a modern and very efficient way which will enable us to mine it and automatically draw conclusions. You will be also able to understand solutions associated with various tasks of motivated learning and cognitive intelligence.
Lectures will be supplemented by laboratory and project classes during which you will train and adapt the solution learned during the lectures on various data. Your hard work and practice will enable you not only to obtain expert knowledge and skills but also to develop your own intelligent learning system implementing a few of the most popular and efficient CI methods.
Expected results of taking a part in this course:
Broad knowledge of neural networks, associative and fuzzy systems as well as other intelligent learning systems.
Novel experience and broaden skills in construction, adaptation and training of neural networks and fuzzy systems.
Abbility to construct intelligent learning systems of various kinds.
Good and modern practices in modelling, construction, learning and generalization.
Own intelligent learning system to use in your life or work.
Satisfaction of enrollment to this course.
How this course will be graded?
Detailed information will be available before this course begins.
Horzyk, A., Human-Like Knowledge Engineering, Generalization and Creativity in Artificial Neural Associative Systems, Springer Verlag, AISC 11156, ISSN 2194-5357, ISBN 978-3-319-19089-1, ISBN 978-3-319-19090-7 (eBook), DOI 10.1007/978-3-319-19090-7, Springer, Switzerland, 2016, pp. 39-51.
Horzyk, A., Innovative types and abilities of neural networks based on associative mechanisms and a new associative model of neurons – the invited talk and paper at the International Conference ICAISC 2015, Springer Verlag, LNAI 9119, 2015, pp. 26-38, DOI 10.1007/978-3-319-19324-3_3.