KNOWLEDGE AND DATA MINING

Second cycle degree in DATA SCIENCE

Campus: PADOVA

Language: English

Teaching period: Second Semester

Lecturer: -- --

Number of ECTS credits allocated: 6


Syllabus
Prerequisites: Suggested basic knowledge of logics and statistics.
Examination methods: Final examination based on: written examination or project development.
Course unit contents: (A) Logics for knowledge representation:
(A.i) introduction to propositional logics, syntax, semantics, decision procedure. Satisfiability, weighted satisfiability, and best satisfiability.
(A.ii) First order logics, syntax, semantics, resolution and unification.
(A.iii) Fuzzy logics, syntax, semantics, and reasoning.

(B) statistical relational learning:
(B.i) Graphical models
(B,ii) Markov Logic Networks
(B.iii) Probabilistic prolog,
(B.iii) Logic Tensor Networks