Course Name | Artificial Intelligence |
Code | Semester | Theory (hour/week) | Application/Lab (hour/week) | Local Credits | ECTS |
---|---|---|---|---|---|
IES 503 | Fall/Spring | 3 | 0 | 3 | 7.5 |
Prerequisites | None | |||||
Course Language | English | |||||
Course Type | Elective | |||||
Course Level | Second Cycle | |||||
Mode of Delivery | - | |||||
Teaching Methods and Techniques of the Course | ||||||
Course Coordinator | ||||||
Course Lecturer(s) | ||||||
Assistant(s) | - |
Course Objectives | Artificial Intelligence (AI) is devoted to the computational study of intelligent behavior. The element that the fields of AI have in common is the creation of agents/machines that can "think". This course will cover a broad technical introduction to the techniques that enable agents/computers to behave intelligently: problem solving, representing knowledge, reasoning, learning, perceiving, and interpreting. The bulk of this course reflects this diversity. We will examine the fundamental questions and issues of AI and will explore the essential techniques. In the special topics, several AI applications will be presented. |
Learning Outcomes | The students who succeeded in this course;
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Course Description | Common LISP and Prolog; Intelligent Agents; Problemsolving and Search: uninformed and heuristic search, A*, local search and optimization; Constraint satisfaction problems; Game playing and adversarial search; Logical reasoning. Propositional Logic. Firstorder logic. Inference in firstorder logic; Planning; Reasoning under uncertainty. Bayes rule. Belief networks. Using beliefs to make decisions. Learning beliefs; Special topics: Robotics, Natural Language Processing, Game Theory, other AI applications. |
Related Sustainable Development Goals | |
| Core Courses | |
Major Area Courses | ||
Supportive Courses | ||
Media and Managment Skills Courses | ||
Transferable Skill Courses |
Week | Subjects | Required Materials |
1 | Introduction to AI. Brief history | Artificial Intelligence: A Modern Approach (second edition) by Stuart Russell and Peter Norvig. Chapter 1. |
2 | Introduction to AI & Applications of AI | Artificial Intelligence: A Modern Approach (second edition) by Stuart Russell and Peter Norvig. Chapter 1. |
3 | Introduction to Lisp & Prolog | Lecture notes |
4 | Intelligent Agents | Artificial Intelligence: A Modern Approach (second edition) by Stuart Russell and Peter Norvig.Chapter 2. |
5 | Problem Solving by Search (Informed Search, Uninformed Search, Adversarial Search) | Artificial Intelligence: A Modern Approach (second edition) by Stuart Russell and Peter Norvig. Chapter 3-4-5 |
6 | Constraint Satisfaction Problems & Special Topics: Machine Learning | Artificial Intelligence: A Modern Approach (second edition) by Stuart Russell and Peter Norvig. Chapter 6 |
7 | First Order Logic / Inference in First Order Logic & Special Topic: Robotics | Artificial Intelligence: A Modern Approach (second edition) by Stuart Russell and Peter Norvig. Chapter 8 &9 |
8 | Logical Agents & Special Topics: Natural Language Processing | Artificial Intelligence: A Modern Approach (second edition) by Stuart Russell and Peter Norvig. Chapter 7. |
9 | Uncertainty and Probabilistic Reasoning & Special Topics: Expert Systems | Artificial Intelligence: A Modern Approach (second edition) by Stuart Russell and Peter Norvig. Chapter 13 &14 |
10 | Special Topics:Genetic Algorithms & Information Retrieval | Lecture Notes |
11 | Special Topics: Planning & Computer Vision | Lecture Notes |
12 | Special Topics: Artificial Neural Networks | Lecture Notes |
13 | Project Presentations I | - |
14 | Project Presentations II | |
15 | Discussions- Review | |
16 | - |
Course Notes/Textbooks | The textbook referenced above and course slides |
Suggested Readings/Materials | Related Research Papers |
Semester Activities | Number | Weigthing |
Participation | ||
Laboratory / Application | ||
Field Work | ||
Quizzes / Studio Critiques | ||
Portfolio | ||
Homework / Assignments | 1 | 25 |
Presentation / Jury | 1 | 25 |
Project | 1 | 50 |
Seminar / Workshop | - | - |
Oral Exam | ||
Midterm | ||
Final Exam | ||
Total |
Weighting of Semester Activities on the Final Grade | 100 | |
Weighting of End-of-Semester Activities on the Final Grade | ||
Total |
Semester Activities | Number | Duration (Hours) | Workload |
---|---|---|---|
Course Hours (Including exam week: 16 x total hours) | 16 | 3 | 48 |
Laboratory / Application Hours (Including exam week: 16 x total hours) | 16 | ||
Study Hours Out of Class | 15 | 4 | 60 |
Field Work | |||
Quizzes / Studio Critiques | |||
Portfolio | |||
Homework / Assignments | 1 | 30 | |
Presentation / Jury | 1 | 35 | |
Project | 1 | 52 | |
Seminar / Workshop | |||
Oral Exam | |||
Midterms | |||
Final Exams | - | ||
Total | 225 |
# | Program Competencies/Outcomes | * Contribution Level | ||||
1 | 2 | 3 | 4 | 5 | ||
1 | To develop and deepen his/her knowledge on theories of mathematics and statistics and their applications in level of expertise, and to obtain unique definitions which bring innovations to the area, based on master level competencies, | |||||
2 | To have the ability of original, independent and critical thinking in Mathematics and Statistics and to be able to develop theoretical concepts, | |||||
3 | To have the ability of defining and verifying problems in Mathematics and Statistics, | |||||
4 | With an interdisciplinary approach, to be able to apply theoretical and applied methods of mathematics and statistics in analyzing and solving new problems and to be able to discover his/her own potentials with respect to the application, | |||||
5 | In nearly every fields that mathematics and statistics are used, to be able to execute, conclude and report a research, which requires expertise, independently, | |||||
6 | To be able to evaluate and renew his/her abilities and knowledge acquired in the field of Applied Mathematics and Statistics with critical approach, and to be able to analyze, synthesize and evaluate complex thoughts in a critical way, | |||||
7 | To be able to convey his/her analyses and methods in the field of Applied Mathematics and Statistics to the experts in a scientific way, | |||||
8 | To be able to use national and international academic resources (English) efficiently, to update his/her knowledge, to communicate with his/her native and foreign colleagues easily, to follow the literature periodically, to contribute scientific meetings held in his/her own field and other fields systematically as written, oral and visual. | |||||
9 | To be familiar with computer software commonly used in the fields of Applied Mathematics and Statistics and to be able to use at least two of them efficiently, | |||||
10 | To contribute the transformation process of his/her own society into an information society and the sustainability of this process by introducing scientific, technological, social and cultural advances in the fields of Applied Mathematics and Statistics, | |||||
11 | As having rich cultural background and social sensitivity with a global perspective, to be able to evaluate all processes efficiently, to be able to contribute the solutions of social, scientific, cultural and ethical problems and to support the development of these values, | |||||
12 | As being competent in abstract thinking, to be able to connect abstract events to concrete events and to transfer solutions, to analyze results with scientific methods by designing experiment and collecting data and to interpret them, | |||||
13 | To be able to produce strategies, policies and plans about systems and topics in which mathematics and statistics are used and to be able to interpret and develop results, | |||||
14 | To be able to evaluate, argue and analyze prominent persons, events and phenomena, which play an important role in the development and combination of the fields of Mathematics and Statistics, within the perspective of the development of other fields of science, | |||||
15 | In Applied Mathematics and Statistics, to be able to sustain scientific work as an individual or a group, to be effective in all phases of an independent work, to participate decision-making process and to make and execute necessary planning within an effective time schedule. |
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest