Information Package
baskent.edu.tr

Master's of Information Technology and System Management without Thesis

BTS553

KNOWLEDGE BASED SYSTEMS

Course Code
BTS553
Semester
-
Theory+Practice
3 + 0
ECTS
10
Course TypeElective Course
Course LevelMaster's Degree Without Thesis
Year of Study-
Semester-
ECTS10
Name of Lecturer(s) -
Learning Outcomes

At the end of this course, the students;

  1. Gain a thorough knowledge of the field of Artificial Intelligence
  2. Understand the emerging approaches in AI and their implications for information engineering
  3. Demonstrate understanding of the applications of AI in business and industry.
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme ComponentsThere is no recommended optional programme component for this course.
Course DescriptionAnalytic tools and theories ok micro economics, theories of producer and consumer , determining the relative prices in different markets, existence and stability of price equilibrium; analysis of welfare and general equilibrium.
Course Contents
WEEK TOPICS
1st Week Basic concepts, Definition of AI, Overview of application areas
2nd Week Problems and problem solving, State space search, Production rules, Logic, Heuristic search techniques, Generate and test, Hill climbing, search reduction strategies
3rd Week Representation models, Predicate Logic, Rules, Semantic Nets, Frames, Conceptual graphs
4th Week Scripts, Fuzziness and uncertainty
5th Week Fuzzy logic, Statistical techniques for determining probability
6th Week Methodologies for developing knowledge based systems, The KBS development life cycle, knowledge acquisition and elicitation, Management of KBS projects, Prototyping, Implementation, Development environments
7th Week MIDTERM
8th Week Neural networks, Architectures, Hopfield network, Multi-layer perception, Feedforward, Backpropagation,
9th Week Genetic Algorithms, Basic concepts, Population, Chromosomes, Operators
10th Week Schemata, Coding, Rule induction, Basic concepts, Decision tree/rule sets
11th Week Major application areas
12th Week Expert systems, Natural language processing
13th Week Machine vision and robotics
14th Week Data mining and intelligent business support, Internet based application
Recommended or Required ReadingPeter Jackson, Introduction to Expert Systems, Addison-Wesley (3rd Ed), 1998, ISBN: 0201876868
Goldberg D. E., Genetic Algorithms in Search, Optimisation and Machine Learning, Addison-Wesley, 1989, ISBN: 0201157675
Michalski, Bratko, Kubat, Machine Learning and Data Mining, Wiley (3rd Ed), 1999, ISBN: 0471971995
A Bradford, Knowledge Engineering and Management: The CommonKADS Methodology, ISBN-10: 0262193000, ISBN-13: 978-0262193009
Expert Systems: Principles and Programming (Hardcover) Publisher: Course Technology; 4Rev Ed edition (15 Oct 2004), ISBN-10: 0534384471, ISBN-13: 978-0534384470
Planned Learning Activities and Teaching Methods
  • Lecture
  • Questions/Answers
  • Problem Solving
  • Other
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 30
Assignment 1 10
Project 1 10
Total(%) 50
Contribution of In-term Studies to Overall Grade(%) 50
Contribution of Final Examination to Overall Grade(%) 50
Total(%) 100
Language of InstructionTurkish
Work Placement(s)No

Programme Qualifications / Learning Outcomes

LO1 LO2 LO3
K1 X X X
K2
K3
K4
K5 X X X
K6
K7
K8 X X X
K9 X X
K10 X
K11 X X