International Teaching | COMPUTER SCIENCE
International Teaching COMPUTER SCIENCE
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cod. SC23200015
COMPUTER SCIENCE
| SC23200015 | |
| DEPARTMENT OF POLITICAL AND COMMUNICATION SCIENCES | |
| EQF7 | |
| DIGITAL MARKETING | |
| 2025/2026 |
| OBBLIGATORIO | |
| YEAR OF COURSE 1 | |
| YEAR OF DIDACTIC SYSTEM 2024 | |
| AUTUMN SEMESTER |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| INF/01 | 6 | 40 | LESSONS |
| Objectives | |
|---|---|
| THE COURSE PROVIDES AN INTRODUCTION TO THE MAIN METHODS AND TECHNIQUES OF ARTIFICIAL INTELLIGENCE MODELING (BOTH SYMBOLIC AND CONNECTIONIST), WITH A SPECIFIC FOCUS ON KNOWLEDGE REPRESENTATION AND MANAGEMENT SYSTEMS BASED ON ONTOLOGIES, KNOWLEDGE GRAPHS, AND LINKED DATA. BY THE END OF THIS COURSE, STUDENTS SHOULD BE ABLE TO: APPLY A COMPUTATIONAL APPROACH TO PROBLEM-SOLVING, ENABLING THEM TO WRITE SHORT PROGRAMS UNDERSTAND THE DIFFERENCE BETWEEN NEURAL AND SYMBOLIC ARTIFICIAL INTELLIGENCE SYSTEMS DESIGN KNOWLEDGE REPRESENTATION AND MANAGEMENT SYSTEMS THAT CAN SERVE AS DECISION SUPPORT SYSTEMS |
| Prerequisites | |
|---|---|
| NONE, BUT A BASIC KNOWLEDGE OF LOGIC AND STATISTICS IS PREFERABLE |
| Contents | |
|---|---|
| INTRODUCTION TO ARTIFICIAL INTELLIGENCE MODELING PARADIGMS (CONNECTIONIST, SYMBOLIC, AND HYBRID MODELS). KNOWLEDGE REPRESENTATION IN AI: HISTORICAL OVERVIEW (SEMANTIC NETWORKS, FRAMES, PRODUCTION RULES). INTRODUCTION TO ONTOLOGIES AND ONTOLOGICAL REASONING SYSTEMS. THE LINKED DATA PARADIGM AND LINKED OPEN DATA: STANDARDS (SKOS) AND RESOURCES (VOCABULARIES). QUERYING RDF KNOWLEDGE BASES WITH SPARQL. LARGE LANGUAGE MODELS AND ONTOLOGIES FOR DECISION SUPPORT SYSTEMS |
| Teaching Methods | |
|---|---|
| LECTURES |
| Verification of learning | |
|---|---|
| PROJECT + ORAL EXAM |
| Texts | |
|---|---|
| LIETO A. COGNITIVE DESIGN FOR ARTIFICIAL MINDS, ROUTLEDGE/TAYLOR & FRANCIS (2021) |
BETA VERSION Data source ESSE3
