Study programme 2023-2024Français
Advanced topics in Artificial Intelligence
Learning Activity
CodeLecturer(s)Associate Lecturer(s)Subsitute Lecturer(s) et other(s)Establishment
I-ILIA-027
  • DUPONT Stéphane
      • UMONS
      Language
      of instruction
      Language
      of assessment
      HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term
      Anglais, FrançaisAnglais, Français1818000Q1


      Content of Learning Activity

      This course deals with the field at the intersection of artificial intelligence and probability theory: probabilistic graphical models, Bayesian networks, and their implementation through probabilistic programming. Decision-making in the face of uncertainty (missing information, noisy data, etc.) by statistical inference constitutes one of the major contributions of applied statistics to AI. This course will offer the following content:
      - Theoretical reminders on the theory of probabilities and applied statistics,
      - General theory of probabilistic graphical models and Bayesian networks,
      - Theory of commonly used models: HMMs (hidden Markov models), particle filters, unsupervised grouping methods (clustering with continuous and discrete variables),
      - Learning / inference methods with these models: inference and learning with so-called hidden variables (not measurable but important for classification or decision-making), Monte-Carlo simulation, Expectation-Maximization (EM) algorithm, IA and generative models.

      This course will include practicals to acquire the theory.
       

      Required Learning Resources/Tools

      All learning resources and tools required for this cours are available via Moodle, the online e-learning platform of UMONS.

      Recommended Learning Resources/Tools

      Additional recommended material is also accessible through Moodle, the online e-learning platform of UMONS.

      Other Recommended Reading

      Not applicable

      Mode of delivery

      • Face-to-face

      Type of Teaching Activity/Activities

      • Cours magistraux
      • Travaux pratiques
      • Travaux de laboratoire
      • Projet sur ordinateur

      Evaluations

      The assessment methods of the Learning Activity (AA) are specified in the course description of the corresponding Educational Component (UE)

      Location of learning activity

      • Université de Mons - Mons

      Location of assessment

      • Université de Mons - Mons
      (*) HT : Hours of theory - HTPE : Hours of in-class exercices - HTPS : hours of practical work - HD : HMiscellaneous time - HR : Hours of remedial classes. - Per. (Period), Y=Year, Q1=1st term et Q2=2nd term
      Date de dernière mise à jour de la fiche ECTS par l'enseignant : 09/05/2023
      Date de dernière génération automatique de la page : 18/05/2024
      20, place du Parc, B7000 Mons - Belgique
      Tél: +32 (0)65 373111
      Courriel: info.mons@umons.ac.be