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Decision making with artificial and computational intelligence

1BM120

Over deze cursus

In modern businesses, the extraction of information from the data in the information systems has become a competitive advantage. The availability of large amounts of data of different modalities (i.e. big data) often requires the use of advanced analytics, computational models and intelligent methods for discovering the relevant information that a business needs. In this course, students are introduced to the advanced data analysis methods from computational and artificial intelligence. Many models must be adaptive to the data and the underlying processes that generate the data. Adaptive and learning models based on neural networks are discussed for exploiting the past information in order to improve the design of information systems for business processes by providing them with knowledge about past business experience and, consequently, to improve their decision support capability. In this context, we will also discuss different approaches to learning, such as supervised, unsupervised, and deep learning. Deep reinforcement learning, which combines deep learning and reinforcement learning, is considered for solving sequential decision-making problems. Optimization of operational processes through nature-inspired meta-heuristics (based on evolutionary computation, swarm intelligence, and multi-objective optimization techniques) is considered.

Leerresultaten

After following this course, the student is able to:

  • discuss how computational and artificial intelligence techniques can support decision making frameworks in different business environments;
  • use deep neural networks, reinforcement learning and evolutionary computation to learn from past business experiences and generate new understanding and knowledge;
  • apply nature-inspired meta-heuristics for optimization of operational processes.

Veronderstelde voorkennis

Je moet voldoen aan één van de onderstaande verzamelingen met eisen

  • Verzameling 1
  • Bachelor of Science (BSc) afgerond
  • Verzameling 2
  • Schakelprogramma afgerond

Link naar meer informatie

Als er nog iets onduidelijk is, kijk even naar de FAQ van TU Eindhoven.

Aanbod

  • Startdatum

    22 april 2024

    • Einddatum
      23 juni 2024
    • Periode *
      Blok GS4
    • Locatie
      Eindhoven
    • Voertaal
      Engels
    Inschrijvingsperiode gesloten
  • Startdatum

    21 april 2025

    • Einddatum
      22 juni 2025
    • Periode *
      Blok GS4
    • Locatie
      Eindhoven
    • Voertaal
      Engels
    De inschrijving begint over 216 dagen
Dit aanbod is voor studenten van Utrecht University