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Information
| Code | CEN348 |
| Name | Artificial Intelligence Systems |
| Term | 2024-2025 Academic Year |
| Semester | 6. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 5 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Doç. Dr. MUSTAFA ORAL |
| Course Instructor |
1 2 |
Course Goal / Objective
Knowledge representation. Search and intuitive programming. Logic and logic programming. Applications of artificial intelligence: Problem solving, games and puzzles, expert systems, planning, learning, pattern recognition, natural language understanding.
Course Content
Representation of knowledge. Search and heuristic programming. Logic and logic programming. Application areas of artificial intelligence: Problem solving, games and puzzles, expert systems, planning, learning, vision, and natural language understanding. Exercises in an artificial intelligence language
Course Precondition
None
Resources
1 Nabiyev V. V., 2005 Yapay Zeka: Problemler, Yöntemler, Algoritmalar, Ankara (2. Baskı) 2 Russell, Stuart J. ; Norvig, Peter, 2003 , Artificial Intelligence: A Modern Approach (2nd ed. )
Notes
1 Nilsson, Nils,1998 , Artificial Intelligence: A New Synthesis, Morgan Kaufmann Publishers, ISBN 978-1-55860-467-4
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Learns basic concepts and algorithms of artificial intelligence. |
| LO02 | Learns probabilistic solutions suitable for uncertainties. |
| LO03 | Understands the difference between supervised and unsupervised learning. Can select the appropriate algorithm for a given problem. |
| LO04 | Learns the working principles of artificial neural networks. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Adequate knowledge of mathematics, science and related engineering disciplines; ability to use theoretical and applied knowledge in these fields in solving complex engineering problems. | |
| PLO02 | Bilgi - Kuramsal, Olgusal | Ability to identify, formulate and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose. | 5 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions; ability to apply modern design methods for this purpose. | |
| PLO04 | Bilgi - Kuramsal, Olgusal | Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering practice; ability to use information technologies effectively. | |
| PLO05 | Bilgi - Kuramsal, Olgusal | Ability to design and conduct experiments, collect data, analyze and interpret results to investigate complex engineering problems or discipline-specific research topics. | 5 |
| PLO06 | Bilgi - Kuramsal, Olgusal | Ability to work effectively in interdisciplinary and multidisciplinary teams; individual working skills. | |
| PLO07 | Bilgi - Kuramsal, Olgusal | Ability to communicate effectively verbally and in writing; knowledge of at least one foreign language; ability to write effective reports and understand written reports, prepare design and production reports, make effective presentations, and give and receive clear and understandable instructions. | |
| PLO08 | Bilgi - Kuramsal, Olgusal | Awareness of the necessity of lifelong learning; ability to access information, follow developments in science and technology, and constantly renew oneself. | |
| PLO09 | Bilgi - Kuramsal, Olgusal | Knowledge of ethical principles, professional and ethical responsibility, and standards used in engineering practice. | |
| PLO10 | Bilgi - Kuramsal, Olgusal | Knowledge of business practices such as project management, risk management and change management; awareness of entrepreneurship and innovation; knowledge of sustainable development. | |
| PLO11 | Bilgi - Kuramsal, Olgusal | Knowledge of the effects of engineering practices on health, environment and safety in universal and social dimensions and the problems of the age reflected in the field of engineering; awareness of the legal consequences of engineering solutions. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Search Problems, Minimax | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 2 | Propositional Logic, Inference | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 3 | Entailment, Model Checking | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 4 | Resolution, First Order Logic | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 5 | Probability, Independence | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 6 | Bayes' Rule, Markov Models | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 7 | Local Search, Simulated Annealing | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 8 | Mid-Term Exam | Exam preparation | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Linear Programming, Backtracking Search | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 10 | Data Collecting, Supervised Learning | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 11 | Nearest-Neighbor Classification, Perceptron Learning | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 12 | Support Vector Machines, Regression, Loss Functions | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 13 | Overfitting, Markov Decision Processes, K-Means Clustering | Reading the lecture notes | Öğretim Yöntemleri: Gösterip Yaptırma, Bireysel Çalışma, Proje Temelli Öğrenme |
| 14 | Artificial Neural Networks | Reading the lecture notes | Öğretim Yöntemleri: Gösterip Yaptırma, Proje Temelli Öğrenme , Bireysel Çalışma |
| 15 | Language, Syntax, Transformers | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma, Soru-Cevap, Örnek Olay |
| 16 | Term Exams | Exam preparation | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | Exam preparation | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 3 | 42 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 12 | 12 |
| Final Exam | 1 | 18 | 18 |
| Total Workload (Hour) | 114 | ||
| Total Workload / 25 (h) | 4,56 | ||
| ECTS | 5 ECTS | ||