Course Name Code Semester T+U Hours Credit ECTS
Artificial Intelligence and Applications SWE 308 6 3 + 0 3 5
Precondition Courses
Recommended Optional Courses
Course Language English
Course Level Bachelor's Degree
Course Type Compulsory
Course Coordinator Dr.Öğr.Üyesi GÖZDE YOLCU ÖZTEL
Course Lecturers
Course Assistants
Course Category Field Proper Education
Course Objective

The objective of the course is to present an overview of artificial intelligence (AI) principles and approaches. Develop a basic understanding of the building blocks of AI as presented in terms of intelligent agents: Search, Knowledge representation, inference, logic, and learning.

Course Content

Introduction to LISP. Intelligent agents. Searching as a problem-solving technique. Knowledge-based agents and logical problem solving. First-order logic as a basis for building intelligent agents capable of acting and reacting in a complex environment. Semantic Networks, Frames, and Description Logics.  Introduction to knowledge graphs and the Semantic Web.  Knowledge engineering. Uncertainty representation and management. Learning agents

# Course Learning Outcomes Teaching Methods Assessment Methods
1 Lecture, Question-Answer, Drilland Practice, Testing, Homework, Project / Design,
2 Lecture, Question-Answer, Drilland Practice, Testing, Homework, Project / Design,
3 Lecture, Question-Answer, Drilland Practice, Testing, Homework, Project / Design,
Week Course Topics Preliminary Preparation
1 Introduction to Artificial Intelligence Weekly presentations
2 Introduction to LISP: basic LISP primitives, procedure definition and binding, predicates and conditionals, procedure and data abstraction, mapping. Weekly presentations
3 Intelligent agents: a discussion on what Artificial Intelligence is about and different types of AI agents. Weekly presentations
4 Searching as a problem-solving technique: a review of "conventional" searching methods including breadth-first, depth-first, bi-directional and best-first search. Weekly presentations
5 Heuristic functions and their effect on performance of search algorithms. Introduction to genetic algorithms. Weekly presentations
6 Knowledge-based agents and logical problem solving Weekly presentations
7 introduction to knowledge representation and propositional logic. Weekly presentations
8 First-order logic as a basis for building intelligent agents capable of acting and reacting in a complex environment Weekly presentations
9 First-order logic as a basis for building intelligent agents capable of acting and reacting in a complex environment Weekly presentations
10 Semantic Networks, Frames, and Description Logics. Weekly presentations
11 Semantic Networks, Frames, and Description Logics. Weekly presentations
12 Knowledge engineering: building knowledge bases and automated theorem provers. Weekly presentations
13 Uncertainty representation and management Weekly presentations
14 Learning agents: learning from observations and examples. Decision trees and the ID3 algorithm. Weekly presentations
Resources
Course Notes <p>Stuard Russell and Peter Norvig, Artificial Intelligence. &nbsp;A Modern Approach, 3-rd edition, Prentice Hall, Inc., 2010</p>
Course Resources

Stuard Russell and Peter Norvig, Artificial Intelligence.  A Modern Approach, 3-rd edition, Prentice Hall, Inc., 2010

Order Program Outcomes Level of Contribution
1 2 3 4 5
1 To have sufficient foundations on engineering subjects such as science and discrete mathematics, probability/statistics; an ability to use theoretical and applied knowledge of these subjects together for engineering solutions.
2 An ability to determine, describe, formulate and solve engineering problems; for this purpose, an ability to select and apply proper analytic and modeling methods,al background in describing, formulating, modeling and analyzing the engineering problem, with a consideration for appropriate analytical solutions in all necessary situations.
3 An ability to select and use modern techniques and tools for engineering applications; an ability to use information technologies efficiently.
4 An ability to analyze a system, a component or a process and design a system under real limits to meet desired needs; in this direction, an ability to apply modern design methods.
5 An ability to design, conduct experiment, collect data, analyze and comment on the results and consciousness of becoming a volunteer on research.
6 Understanding, awareness of administration, control, development and security/reliability issues about information technologies.
7 An ability to work efficiently in multidisciplinary teams, self confidence to take responsibility.
8 An ability to present himself/herself or a problem with oral/written techniques and have efficient communication skills; know at least one extra language.
9 An awareness about importance of lifelong learning; an ability to update his/her knowledge continuously by means of following advances in science and technology.
10 Understanding, practicing of professional and ethical responsibilities, an ability to disseminate this responsibility on society.
11 An understanding of project management, workplace applications, health issues of laborers, environment and job safety; an awareness about legal consequences of engineering applications.
12 An understanding universal and local effects of engineering solutions; awareness of entrepreneurial and innovation and to have knowledge about contemporary problems.
Evaluation System
Semester Studies Contribution Rate
1. Ara Sınav 70
1. Ödev 10
1. Kısa Sınav 10
1. Proje / Tasarım 10
Total 100
1. Final 50
1. Yıl İçinin Başarıya 50
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Total Workload 0
Total Workload / 25 (Hours) 0
dersAKTSKredisi 5