This course covers both the basic theory and practical applications of AI which is the science and engineering of producing intelligent agents that can behave rationally. It aims to introduce the undergraduates with the computational models of intelligent behavior, including problem solving, knowledge representation, reasoning, planning, decision making, learning, perception, action, communication and interaction. It emphasizes the techniques outlined as combinatorial search, probabilistic models and reasoning.
Prerequisite(s)
Corequisite(s)
Special Requisite(s)
Instructor(s)
Course Assistant(s)
Schedule
Office Hour(s)
Teaching Methods and Techniques
Principle Sources
Other Sources
Course Schedules
Week
Contents
Learning Methods
1. Week
Introduction to Artificial Intelligence and Intelligence Agents
PRESENTATION AND PRACTICE
2. Week
Solving Problems by searching and Informed search
PRESENTATION AND PRACTICE
3. Week
Solving Problems by searching and Informed search
PRESENTATION AND PRACTICE
4. Week
Constraint Satisfaction and Adversarial Search
PRESENTATION AND PRACTICE
5. Week
Constraint Satisfaction and Adversarial Search
PRESENTATION AND PRACTICE
6. Week
Logical Agents
PRESENTATION AND PRACTICE
7. Week
First Order Logic
PRESENTATION AND PRACTICE
8. Week
Midterm
9. Week
Inference in First Order Logic
PRESENTATION AND PRACTICE
10. Week
Knowledge Representation
PRESENTATION AND PRACTICE
11. Week
Quantifying Uncertainity
PRESENTATION AND PRACTICE
12. Week
Probabilistic Reasoning
PRESENTATION AND PRACTICE
13. Week
Learning From Examples and Decision Trees
PRESENTATION AND PRACTICE
14. Week
Reinforcement Learning
PRESENTATION AND PRACTICE
15. Week
FINAL
16. Week
FINAL
17. Week
FINAL
Assessments
Evaluation tools
Quantity
Weight(%)
Final Exam
1
100
Program Outcomes
PO-1
Effectively identifying collecting and evaluating the data required for the Computer Programming field and using theoretical knowledge for creating applications.
PO-2
Being equipped with basics of computer science.
PO-3
Possessing the knowledge of all necessary software and equipment in the profession.
PO-4
Emphasizing team work, contributing to the group and operating with team chemistry.
PO-5
Effectively expressing and sharing the completed work with project group and teammates.
PO-6
Objectively evaluating the performance of employees under his/her supervision and providing objective information to the management.
PO-7
Demonstrating problem solving skills and the education he/she obtained at the program.
PO-8
Possessing the computer programming knowledge built on skills, information and competencies provided by secondary education and supperted by higher education course materials, and demonstrating the understanding of concepts in the field of computer programming.
PO-9
Acquiring the analytical thinking skills required in the field of computer programming, and creating and running programs in accordance with this analytical perspective.
PO-10
Complying with ethical values of the field of Computer Programming and carrying social responsibility.
PO-11
Developing sufficent foreign language skills to conduct the work and follow the global developments at the best level.
PO-12
Empasizing communication and using Turkish accurately in this communication.
PO-13
Ensuring the security, environment and health awareness at personal level and among his/her employees.
PO-14
Following technological innovations in software and hardware after graduation and sustaining continuous personal development.
PO-15
Claiming responsibility at his/her workplace, organizing work flow with employees and operating according to high quality work standards.
Learning Outcomes
LO-1
Understand the main approaches to artifical intelligence such as heuristic search, game search, logical inference, statistical inference, decision theory, planning, machine learning, neural networks and natural language proccessing
LO-2
Recognize problems that may be solved using artificial intelligence
LO-3
Implement artificial intelligence algorithms for hands-on experiences
LO-4
Explain recent developments in interdisciplinary fields on brain modeling and understanding how to work and assess brain inspired learning algorithms
LO-5
Have some experience gained with homeworks and one term project.
