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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 evaluate resulting models and standards,
  • to formulate the appropriate data utilization mechanisms for 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
  • Mining complex data: text, images, web data, etc.
  • Reinforced Learning
  • Deep Learning
  • Evaluation metrics
  • Problems in Knowledge Discovery

Module’s Address in eClass