Fundamentals of Artificial Intelligence and Data Management Single channel
Chair (Coordinator) and Rapporteur: ANTONELLA POGGI
Lecturers
Objectives
General goals:
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To present the fundamental methods of artificial intelligence that are based on high-level symbolic representations. To introduce the main techniques for searching, the main languages for the representation of knowledge and the associated reasoning mechanisms.
To study of the fundamental aspects of data management systems and database design methodologies. More precisely, the goal is to provide the student with the notions regarding techniques and methods to address database design problems, with emphasis on modeling languages and their formal properties.
Specific goals:
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To address search problems, use languages for knowledge representation, apply the main techniques of symbolic reasoning.
To conduct projects for the creation of databases using the appropriate methodologies and the appropriate languages for data modeling and manipulation
Knowledge and understanding:
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Learning the notion of intelligent agent, automatic search techniques in the space of solutions, mechanisms for knowledge representation, forms of reasoning, logic programming.
Knowledge of data representation models, database management systems, languages to interact with databases, and relational data base design methodologies.
Apply knowledge and understanding:
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Being able to make searches in the space of solutions, define knowledge bases and use automatic reasoning mechanisms over them.
Being able to design relational databases using appropriate methodologies that guarantee correctness and efficiency of the design product.
Critical and judgment skills:
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Knowing how to evaluate the quality of symbolic representation, in terms of expressiveness and computational complexity.
Being able to evaluate the correctness of a data base schema, and the efficiency of a data base against information on the application load that will weigh on the data.
Communication skills:
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Being able to describe the choices made and the design and development methodologies adopted as part of a knowledge base or database project.
Learning ability
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The design activities carried out during the course will stimulate the student to autonomously study some topics presented in the course.
- Academic year2026/2027
- Degree program to which the course belongsMathematical Sciences for Artificial Intelligence
- Lesson code10603316
- Year and semester2nd year - 1st semester
- Activity typeAttività formative caratterizzanti
- Academic areaFormazione Matematica Modellistico-Computazionale
- SSDING-INF/05
- Mandatory presenceNo
- Languageita
- CFU12 CFU
- Total duration96 hours
- Hours distribution60 classroom hours, 36 training hours