Second Cycle Degree Programme in Embedded Computing Systems
Prof.: Beatrice Lazzerini
The objective of this course is to teach the theoretical background and the basic methodologies for developing intelligent systems, i.e., systems that show the remarkable ability to reason and learn in uncertain and imprecise environments.
The student who successfully completes the course will have the ability to design and develop intelligent systems in several application domains.
This course covers the theory and application of a number of computational intelligence methodologies, including artificial neural networks, fuzzy inference systems and genetic algorithms.
The focus is on the design and development of computationally intelligent systems with human-like capabilities in terms of reasoning, learning and adaptation. Special emphasis will be placed on linking computational intelligence techniques to real world applications and projects.
Software tools will be used to illustrate concepts and to design/implement computationally intelligent systems. During the course practical exercises will also be carried out in the laboratory.
face to face
The teacher will provide lecture slides and handouts.
Oral exam (50%) and practical project (50%).
During the oral exam the student will be assessed on his/her demonstrated ability to discuss the main course contents. In the practical project the student must demonstrate the ability to put into practice the methods illustrated during the course.
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