PRINCIPLES OF ARTIFICIAL INTELLIGENCE
- Course
- AIEN201 - PRINCIPLES OF ARTIFICIAL INTELLIGENCE
- Department
- Artificial Intelligence Engineering - English - Undergraduate
- Course Type
- Course
- Status
- Required
- Language
- English
- Credit
- 3
- ECTS
- 6
- T+P+L
- 3 + 0 + 0
- Course Coordinator(s)
- Assoc. Prof. Dr. Emre ÖZBİLGE
- Prerequisite
- -
- Keywords
Course Description
This course aims to present the main concepts and techniques used in Artificial Intelligence (AI) and introduce a range of real-world AI applications. The students will acquire knowledge about the history and the foundations of AI, and the basis required for developing autonomous intelligent agents. By the end of the course students are expected to have the fundamental knowledge on principles of artificial intelligence, develop problem solving skills on various artificial intelligence problems and implement related real world applications. In addition to the topics stated above, the AI students are also expected to gain general knowledge about the development of basic autonomous systems.
PRINCIPLES OF ARTIFICIAL INTELLIGENCE
Evaluation Tools (Active Term)
No evaluation items have been defined.
Course outcomes
No course outcomes have been defined yet.
Course Syllabus
| Week | Topic |
|---|---|
| Week 1 | History to AI: What is AI? Foundation of AI? Sate of the art in AI? Risks and Benefits of AI? |
| Week 2 | Intelligent Agent: Agent and Environments, Concept of Rationality, Nature of Environments, Structure of Agents, Nature of Environments, Structure of Agents |
| Week 3 | Problem Formulation & Uninformed Search |
| Week 4 | Informed Search & Heuristics |
| Week 5 | Constraint Satisfaction Problems (CSPs) |
| Week 6 | Adversarial Search (Games) |
| Week 7 | Knowledge Representation: Logic (Part I) |
| Week 8 | Revision |
| Week 9 | Midterm Exam Week |
| Week 10 | Inference in First-Order Logic (Part II) |
| Week 11 | Uncertinity, Probabilistic Reasoning & Naive Bayes |
| Week 12 | Introduction to Robotics |
| Week 13 | Introduction to Computer Vision |
| Week 14 | Ethics & Societal Impact & Revision |
| Week 15 | Final Exam Week |
Reference Books & Course Materials
- 01 Artificial Intelligence: A Modern Approach 4th edition (2022) – S. Russell & P. Norvig
- 02 Artificial Intelligence: A System Approach (2008) – M.T. Jones
Learning Outcomes
No learning outcomes have been defined.
Program Outcomes
- Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in complex engineering problems.
- Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modelling methods for this purpose.
- Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose.
- Ability to devise, select, and use modern techniques and tools needed for analysing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively.
- Ability to design and conduct experiments, gather data, analyse and interpret results for investigating complex engineering problems or discipline specific research questions.
- Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
- Ability to communicate effectively in Turkish, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions.
- Recognition of the need for lifelong learning ; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
- Consciousness to behave according to ethical principles and professional and ethical responsibility; knowledge on standards used in engineering practice.
- Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development.
- Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions.
Po-Lo Matrix
The PO-LO matrix has not been populated yet.