Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Study Plan
This information is intended exclusively for students already enrolled in this course.If you are a new student interested in enrolling, you can find information about the course of study on the course page:
Laurea magistrale in Artificial Intelligence - Enrollment from 2025/2026The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
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| Modules | Credits | TAF | SSD |
|---|
1 course among the following2 modules among the following (1st year: Knowledge representation, Natural language processing, HCI Intelligent interfaces - 2nd year: AI & Cloud, Visual intelligence, Statistical learning - 1st and 2nd year: Computer Vision & Deep Learning)2 modules among the following (1st year: Knowledge representation, Natural language processing, HCI Intelligent interfaces - 2nd year: AI & Cloud - 1st and 2nd year: Computer Vision & Deep learning)2 courses among the following (A.A. 2023/24: Complex systems and Network Science not activated)Legend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
HCI – Intelligent Interfaces (2023/2024)
Teaching code
4S010680
Credits
6
Language
English
Also offered in courses:
- Interazione Uomo Macchina - FUNDAMENTALS of the course Master's degree in Computer Engineering for Robotics and Smart Industry
- Interazione Uomo Macchina - ADVANCED INTERACTION of the course Master's degree in Computer Engineering for Robotics and Smart Industry
Scientific Disciplinary Sector (SSD)
ING-INF/05 - INFORMATION PROCESSING SYSTEMS
Courses Single
Authorized
The teaching is organized as follows:
Advanced Interaction
Fundamentals
Learning objectives
The course aims to provide fundamental notions for the design and evaluation of interactive systems. The course will introduce basic concepts about usability and user experience, human factors, interaction paradigms, usability engineering and evaluation.
These concepts will be applied on standard and advanced interfaces with particular focus on natural interaction in Virtual and Mixed reality.
At the end of the course, the student will have to demonstrate knowledge and understanding of the basic principles of user-centered interaction design and will be able to apply them to the design of various types of computer interfaces.
He will be also able to develop prototypes of virtual / mixed reality applications, considering the specificities of the interaction and will be able to analyze the usability and the user experience of both standard interfaces and mixed reality applications.
This knowledge will provide the student with the ability to: i) independently assess the usability problems of the systems and select the correct evaluation methods for each different task; ii) expand and deepen the technical knowledge of the various aspects of the AI study path being able to consider the effects of human factors in the use of technology. At the end of the course, the student will also have to show that he is able to: i) design advanced AI-based interfaces design considering human factors
ii) Exploit HCI principles to make AI system understandable and design visualization tools for AI systems
iii) develop interactive 3D environments for usability analysis, training, interaction in mixed reality.
Prerequisites and basic notions
Basic knowledge of statistics and computer graphics
Program
Fundamentals of HCI Cognitive Aspects Humans, Vision and Color
Interaction design
Usability assessment: Data Collection and Data Analysis
Virtual Reality and Mixed Reality: Technologies, Cognitive and Human Aspects, Tracking and Rendering Solutions.
Lab: Prototyping and Prototype Evaluation with Unity
Bibliography
Didactic methods
Lectures and lab sessions
Learning assessment procedures
Oral exam and evaluation of lab activity
Evaluation criteria
To pass the exam, students must demonstrate that they:
- have understood the concepts underlying man-machine interaction and the design of interactive systems
- are able to present their arguments in a precise and organic way;
-know how to apply the acquired knowledge to solve practical problems of design and usability evaluation
Criteria for the composition of the final grade
50% oral 50% lab activity evaluation
Exam language
Inglese o Italiano
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