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Knowledge Discovery end Decision Support Systems

Module ID

E705

Semester

7

Hours/Week - ECTS

4 – 5

Fotios Kokkoras

Assistant Professor

Learning Outcomes

Upon successful completion of the course, the student will be able:

  • to understand the complex and iterative process of knowledge discovery from data,
  • to list the types of knowledge that are generated and the algorithms that perform the mining,
  • to understand and apply machine learning algorithms to data,
  • to perceive under/over-fitting phenomena and deal with them,
  • to apply the above in the context of decision support.

 

Indicative Module Content

  • Knowledge discovery from data – the steps.
  • Predictive Models and Informative Patterns as Tools for Decision Making.
  • Knowledge discovery as an application of machine learning algorithms.
  • Supervised learning:
    • classification,
    • regression.
  • Unsupervised learning
    • clustering,
    • association rules.
  • Neural Networks.
  • Deep Learning, Deep Neural Networks.
  • Evaluation metrics.
  • Problems in Knowledge Discovery.

Module’s Address in eClass