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COMPUTER SCIENCE

International Teaching COMPUTER SCIENCE

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0323200010
DEPARTMENT OF POLITICAL AND COMMUNICATION SCIENCES
EQF7
DIGITAL MARKETING
2024/2025

OBBLIGATORIO
YEAR OF COURSE 1
YEAR OF DIDACTIC SYSTEM 2024
AUTUMN SEMESTER
CFUHOURSACTIVITY
630LESSONS
ANTONIO LIETO T Curriculum
Objectives
THE COURSE PROVIDES AN INTRODUCTION TO THE BASIC CONCEPTS OF PROGRAMMING AND INTRODUCES THE MAIN METHODS AND TECHNIQUES OF
MODELING ARTIFICIAL INTELLIGENCE (BOTH SYMBOLIC AND CONNECTIONIST) WITH A SPECIFIC FOCUS ON ONTOLOGY-BASED KNOWLEDGE REPRESENTATION
AND MANAGEMENT SYSTEMS, KNOWLEDGE GRAPHS, AND LINKED DATA. BY THE END OF THIS COURSE, STUDENTS SHOULD BE ABLE TO:
• HAVE A COMPUTATIONAL APPROACH TO PROBLEM-SOLVING THAT ALLOWS THEM TO WRITE SHORT PROGRAMS
• UNDERSTAND THE DIFFERENCE BETWEEN NEURAL AND SYMBOLIC ARTIFICIAL INTELLIGENCE PROGRAMS
• CREATE KNOWLEDGE REPRESENTATION AND MANAGEMENT SYSTEMS CAPABLE OF ACTING AS DECISION SUPPORT SYSTEMS
Prerequisites
NONE, BUT IT IS PREFERABLE A BASIC KNOWLEDGE OF LOGICS AND STATISTICS
Contents
INTRODUCTION TO THE MAIN MODELLING METHODS AND TECHNIQUES USED IN ARTIFICIAL INTELLIGENCE (AI). KNOWLEDGE REPRESENTATION IN AI. THE BASICS OF DESCRIPTION LOGICS. SEMANTIC WEB TECHNOLOGIES. RDF/OWL LANGUAGES AND ONTOLOGY REASONING. EDITING SIMPLE ONTOLOGIES VIA ONTOLOGY EDITORS. SEMANTIC REASONERS. QUERYING RDF GRAPHS VIA SPARQL. ONTOLOGICAL RESOURCES FOR CULTURAL HERITAGE. SOFTWARE ARCHITECTURES FOR THE SEMANTIC WEB. LINKED DATA PLATFORMS. VISUALIZATION OF DRF GRAPHS, R2RML MAPPING LANGUAGE.
Teaching Methods
LECTURES AND LAB LESSONS.
Verification of learning
DISCUSSION OF PROJECT WORK + ORAL EXAM
Texts
LIETO A. COGNITIVE DESIGN FOR ARTIFICIAL MINDS, ROUTLEDGE/TAYLOR & FRANCIS (2021):
Lessons Timetable

  BETA VERSION Data source ESSE3