Energy Systems Engineering (English) | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code: | BIL396 | ||||||||
Course Name: | Artificial Intelligence | ||||||||
Course Semester: | Fall | ||||||||
Course Credits: |
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Language of instruction: | TR | ||||||||
Course Requisites: | |||||||||
Does the Course Require Work Experience?: | No | ||||||||
Type of course: | Compulsory | ||||||||
Course Level: |
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Mode of Delivery: | Face to face | ||||||||
Course Coordinator : | Dr.Öğr.Üyesi FÜSUN ER | ||||||||
Course Lecturer(s): |
Dr.Öğr.Üyesi ASLI UYAR Prof. Dr. PINAR YILDIRIM |
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Course Assistants: |
Course Objectives: | Introduction to Artificial Intelligence. Heuristic problem solving. State spaces. Serching at state spaces. Games. Minimum spanning tree. Knowledge modeling. Representing knowledge. Logic. Neural networks. Fuzzy Logic. |
Course Content: | Introduction to Artificial Intelligence. Heuristic problem solving. State spaces. Serching at state spaces. Games. Minimum spanning tree. Knowledge modeling. Representing knowledge. Logic. Neural networks. Fuzzy Logic. |
The students who have succeeded in this course;
|
Week | Subject | Related Preparation |
1) | Fundamental concepts of artificial intelligence | |
2) | Machine learning | |
3) | Artificial neural networks | |
4) | Game theory | |
5) | Problem solving: Uninformed search agents | |
6) | Problem solving: Informed search agents | |
7) | Knowledge-based agents: The Wumpus World | |
8) | Midterm | |
9) | Logic and reasoning | |
10) | Logic Programming: Prolog | |
11) | Fundamental concepts about voice and vision recognition | |
12) | Voice recognition using hidden markov models | |
13) | Image recognition based on convolutional neural network. | |
14) | Project presentations |
Course Notes / Textbooks: | Artificial Intelligence: A Modern Approach. Stuart Russell, Peter Norvig, Prentice Hall, Second Edition Yapay Zeka, Prof.Dr.Vasif V.Nabiyev |
References: | Yapay Zeka Geçmişi ve Geleceği, Nils J. Nilson Introduction to Algorithms, Cormen. Makine Öğrenmesi, Ethem Alpaydın |
Learning Outcomes | 1 |
2 |
4 |
5 |
5 |
6 |
7 |
8 |
9 |
10 |
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Program Outcomes | ||||||||||
1) Closed Department |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | Closed Department |
Expression | |
Individual study and homework | |
Lesson | |
Problem Solving | |
Project preparation | |
Report Writing | |
Q&A / Discussion | |
Application (Modelling, Design, Model, Simulation, Experiment etc.) |
Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing) | |
Application | |
Individual Project | |
Presentation | |
Reporting | |
Bilgisayar Destekli Sunum |
Semester Requirements | Number of Activities | Level of Contribution |
Presentation | 1 | % 10 |
Project | 1 | % 30 |
Midterms | 1 | % 20 |
Final | 1 | % 40 |
total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 60 | |
PERCENTAGE OF FINAL WORK | % 40 | |
total | % 100 |
Activities | Number of Activities | Duration (Hours) | Workload |
Course Hours | 13 | 3 | 39 |
Presentations / Seminar | 1 | 3 | 3 |
Project | 1 | 48 | 48 |
Midterms | 1 | 48 | 48 |
Paper Submission | 1 | 12 | 12 |
Final | 1 | 48 | 48 |
Total Workload | 198 |