Information Package

Master's of Computer Engineering without Thesis

BİL551

ARTIFICIAL INTELLIGENCE

Course Code
BİL551
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. Be informed of Knowledge representation and reasoning.
  2. Know syntax, semantics, and proof theory (deductive inference) of propositional logic.
  3. Apply first-order predicate logic.
  4. Have knowledge of uncertainty and probabilistic reasoning.
  5. Recognize expert systems.
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme ComponentsNone
Course DescriptionKnowledge representation and reasoning. Syntax, semantics. Proof theory (deductive inference) of propositional logic. First-order predicate logic. Uncertainty. Probabilistic reasoning. Expert systems.
Course Contents
WEEK TOPICS
1st Week Knowledge representation and reasoning.
2nd Week Knowledge representation and reasoning.
3rd Week Knowledge representation and reasoning.
4th Week Syntax, semantics.
5th Week Syntax, semantics.
6th Week Syntax, semantics.
7th Week Syntax, semantics.
8th Week Mid-term
9th Week Proof theory (deductive inference) of propositional logic. First-order predicate logic.
10th Week Proof theory (deductive inference) of propositional logic. First-order predicate logic.
11th Week Uncertainty.
12th Week Probabilistic reasoning.
13th Week Expert systems.
14th Week Expert systems.
Recommended or Required Reading1. Russell S., Norvig P. Artificial Intelligence: A Modern Approach, Prentice Hall, 2003, Second Edition, ISBN: 9780137903955
Planned Learning Activities and Teaching Methods
  • Lecture
  • Questions/Answers
  • Presentation
  • Experiment
  • Practice
  • Problem Solving
  • Project
  • Report Preparation
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 30
Assignment 1 15
Project 1 15
Total(%) 60
Contribution of In-term Studies to Overall Grade(%) 60
Contribution of Final Examination to Overall Grade(%) 40
Total(%) 100
ECTS Allocated Based on Student Workload
Activities Quantity Duration (Hour) Total Workload (Hour)
Midterm exam 1 2 2
Preparation for Quiz
Individual or group work
Preparation for Final exam 1 70 70
Course hours 14 3 42
Preparation for Midterm exam 1 50 50
Laboratory (including preparation)
Final exam 1 2 2
Homework 3 30 90
Project 1 35 35
Total Work Load291
Total Work Load / 30 (h)9.7
ECTS Credit of the Course10
Language of InstructionTurkish
Work Placement(s)No
LO1 LO2 LO3 LO4 LO5
K1 X X X
K2 X X
K3 X X
K4 X X
K5 X X
K6 X
K7 X
K8 X X X X
K9
K10 X
K11 X
K12 X