DECISION SUPPORT THEORY AND SYSTEMS

Course Information
TitleΘΕΩΡΙΑ ΚΑΙ ΣΥΣΤΗΜΑΤΑ ΛΗΨΗΣ ΑΠΟΦΑΣΕΩΝ / DECISION SUPPORT THEORY AND SYSTEMS
CodeNIS-06-01
FacultySciences
SchoolInformatics
Cycle / Level1st / Undergraduate
Teaching PeriodSpring
CoordinatorIoannis Vlachavas
CommonNo
StatusActive
Course ID40002949

Programme of Study: PPS-Tmīma Plīroforikīs (2019-sīmera)

Registered students: 147
OrientationAttendance TypeSemesterYearECTS
GENIKĪ KATEUTHYNSĪYPOCΗREŌTIKO KATA EPILOGĪ635

Class Information
Academic Year2020 – 2021
Class PeriodSpring
Faculty Instructors
Weekly Hours3
Class ID
600180181
Course Type 2016-2020
  • Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Examination)
Prerequisites
General Prerequisites
Basic knowledge of probability theory.
Learning Outcomes
Cognitive: Understanding the basic theory for simple and sequential decisions by an intelligent agent, familiarization with the types of decision support systems, understanding the theory of decision making with data analysis, understanding the basic principles of game theory, understanding computational issues in developing decision support systems, familiarization with the use of decision support software. Skills: Training on developing decision support systems, training on the use of decision support tools.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Make decisions
  • Work autonomously
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Introduction, Decision Making under Certainty (Multi-criteria Decision Making Methods), Decision Making under Ignorance, Decision Making under Risk (Probability Theory, Bayesian Networks, Utility Theory), Sequential Decisions (Decision Trees), Decision Making in the presence of Competitive Agents (Game Theory), Decision Making with Data Analysis (Machine Learning, Knowledge Discovery in Databases, Business Intelligence.
Educational Material Types
  • Notes
  • Slide presentations
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Communication with Students
  • Use of ICT in Student Assessment
Description
Use of email and elearning system Lectures' slides
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures52
Reading Assigment85
Written assigments10
Exams3
Total150
Student Assessment
Description
Final Exams (at the end of the semester). Quizes with multiple choice questions. Bonus grades from projects. The evaluation criteria are mentioned in the course webpages.
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Summative)
  • Written Exam with Short Answer Questions (Summative)
  • Written Exam with Extended Answer Questions (Summative)
  • Written Assignment (Summative)
  • Written Exam with Problem Solving (Summative)
Bibliography
Course Bibliography (Eudoxus)
i) Τεχνητή Νοημοσύνη: Μια σύγχρονη προσέγγιση, S Russel, P. Norvig, ΚΛΕΙΔΑΡΙΘΜΟΣ, ISBN: 9602098732, ii)Τεχνητή Νοημοσύνη, Ι. Βλαχάβας, Π. Κεφαλάς, Ν. Βασιλειάδης, Φ. Κόκκορας, Η. Σακελλαρίου, Γ' Έκδοση, Εκδόσεις Πανεπιστημίου Μακεδονίας, 2011, ISBN: 978-960-8396-64-7
Additional bibliography for study
Σημειώσεις μαθήματος σε ηλεκτρονική μορφή Διαφάνειες μαθήματος σε ηλεκτρονική μορφή
Last Update
11-02-2020