Faculty Of Engıneerıng
Electrıcal And Electronıcs Engıneerıng (Englısh)
Course Information
| ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING | |||||
|---|---|---|---|---|---|
| Code | Semester | Theoretical | Practice | National Credit | ECTS Credit |
| Hour / Week | |||||
| CSE419 | Fall | 3 | 0 | 3 | 5 |
| Prerequisites and co-requisites | |
|---|---|
| Language of instruction | English |
| Type | Elective |
| Level of Course | Bachelor's |
| Lecturer | Asst. Prof. Furkan GÖZÜKARA |
| Mode of Delivery | Face to Face |
| Suggested Subject | |
| Professional practise ( internship ) | None |
| Objectives of the Course | The purpose of this course is to teach the basic principles of engineering applications of artificial intelligence techniques used and their applications to perform detailed analysis of how is used. |
| Contents of the Course | Artificial intelligence definition, basic concepts and techniques, Expert systems and engineering applications, Fuzzy logic and engineering applications, Decision support systems and applications, Genetic algorithms and application examples, Artificial neural networks: structure and basic elements of artificial neural networks, the first artificial neural networks, artificial neural network models, back propagation networks. Engineering applications of artificial neural networks. |
Learning Outcomes of Course
| # | Learning Outcomes |
|---|---|
| 1 | The student learns the basic principles of artificial intelligence. Understand approaches to the implementation of artificial intelligence techniques to engineering problems. |
| 2 | Student understands the basic principles of fuzzy logic and describes engineering applications. |
| 3 | Student understands the basic principles of expert systems and describes engineering applications. |
| 4 | Student understands the basic principles of decision support systmes and describes engineering applications. |
Course Syllabus
| # | Subjects | Teaching Methods and Technics |
|---|---|---|
| 1 | Introduction to Artificial Intelligence | Lecture |
| 2 | Presentation of Art.Int. in Eng. Appl. | Lecture |
| 3 | Expert Systems | Lecture |
| 4 | Expert Systems and engineering application | Lecture |
| 5 | Fuzzy Logic Basics | Lecture |
| 6 | Fuzzy logic and Engineering Applications | Lecture |
| 7 | Midterm | |
| 8 | Decision support systems | Lecture |
| 9 | Neural Networks | Lecture |
| 10 | Neural Networks | Lecture |
| 11 | Neural Networks in engineering applications | Lecture |
| 12 | Genetic Algorithms | Lecture |
| 13 | Genetic Algorithms | Lecture |
| 14 | Genetic Algorithms in engineering applications | Lecture |
| 15 | Hybrid techniques (fuzzy-neuro, fuzzy-genetic) | Lecture |
| 16 | Final Exam |
Course Syllabus
| # | Material / Resources | Information About Resources | Reference / Recommended Resources |
|---|---|---|---|
| 1 | Artificial Intelligence: A Modern Approach (3rd ed) by Stuart Russell and Peter Norvig |
Method of Assessment
| # | Weight | Work Type | Work Title |
|---|---|---|---|
| 1 | 40% | Mid-Term Exam | Mid-Term Exam |
| 2 | 60% | Final Exam | Final Exam |
Relationship between Learning Outcomes of Course and Program Outcomes
| # | Learning Outcomes | Program Outcomes | Method of Assessment |
|---|---|---|---|
| 1 | The student learns the basic principles of artificial intelligence. Understand approaches to the implementation of artificial intelligence techniques to engineering problems. | 1 | 1͵2 |
| 2 | Student understands the basic principles of fuzzy logic and describes engineering applications. | 3 | 1͵2 |
| 3 | Student understands the basic principles of expert systems and describes engineering applications. | 12 | 1͵2 |
| 4 | Student understands the basic principles of decision support systmes and describes engineering applications. | 15 | 1͵2 |
Work Load Details
| # | Type of Work | Quantity | Time (Hour) | Work Load |
|---|---|---|---|---|
| 1 | Course Duration | 14 | 3 | 42 |
| 2 | Course Duration Except Class (Preliminary Study, Enhancement) | 0 | 0 | 0 |
| 3 | Presentation and Seminar Preparation | 0 | 0 | 0 |
| 4 | Web Research, Library and Archival Work | 0 | 0 | 0 |
| 5 | Document/Information Listing | 0 | 0 | 0 |
| 6 | Workshop | 0 | 0 | 0 |
| 7 | Preparation for Midterm Exam | 0 | 0 | 0 |
| 8 | Midterm Exam | 0 | 0 | 0 |
| 9 | Quiz | 0 | 0 | 0 |
| 10 | Homework | 0 | 0 | 0 |
| 11 | Midterm Project | 0 | 0 | 0 |
| 12 | Midterm Exercise | 0 | 0 | 0 |
| 13 | Final Project | 1 | 38 | 38 |
| 14 | Final Exercise | 0 | 0 | 0 |
| 15 | Preparation for Final Exam | 0 | 0 | 0 |
| 16 | Final Exam | 1 | 45 | 45 |
| 125 | ||||