Advanced Electronics and Communication Technology (English) with thesis | |||||
Master | TR-NQF-HE: Level 7 | QF-EHEA: Second Cycle | EQF-LLL: Level 7 |
Course Code: | AIE503 | ||||||||
Course Name: | Introduction to AI Engineering | ||||||||
Course Semester: | Spring | ||||||||
Course Credits: |
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Language of instruction: | EN | ||||||||
Course Requisites: | |||||||||
Does the Course Require Work Experience?: | No | ||||||||
Type of course: | Department Elective | ||||||||
Course Level: |
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Mode of Delivery: | Face to face | ||||||||
Course Coordinator : | Prof. Dr. BEKİR TEVFİK AKGÜN | ||||||||
Course Lecturer(s): |
Dr.Öğr.Üyesi SİNA ALP |
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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;
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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 |
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5 |
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10 |
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Program Outcomes | |||||||||||
1) By carrying out scientific research in their field, graduates evaluate and interpret deeply and broadly, their findings and apply their findings. | |||||||||||
2) Graduates have extensive knowledge about current techniques and methods applied in engineering and their limitations. | |||||||||||
3) Graduates can complet and implement knowledge using scientific methods using limited or incomplete data; can use the information of different disciplines together. | |||||||||||
4) Graduates are aware of new and evolving practices of their profession, examinining new knowledge and learning as necessary | |||||||||||
5) Graduates can define and formulate problems related to the field, develop methods to solve them and apply innovative methods in solutions. | |||||||||||
6) Graduates develop new and/or original ideas and methods; design complex systems or processes and develop innovative / alternative solutions in their designs. | |||||||||||
7) Graduates design and apply theoretical, experimental and model-based research; analyze and investigate the complex problems encountered in this process. | |||||||||||
8) Lead in multidisciplinary teams, develop solution approaches in complex situations, work independently and take responsibility. | |||||||||||
9) A foreign language communicates verbally and in writing using at least the European Language Portfolio B2 General Level. | |||||||||||
10) Transfers the processes and outcomes of their work in a systematic and explicit manner, either written or verbally, in the national or international contexts of that area. | |||||||||||
11) Recognize the social, environmental, health, safety, legal aspects of engineering applications, as well as project management and business life practices, and are aware of the limitations they place on engineering applications. | |||||||||||
12) Consider social, scientific and ethical values in the collection, interpretation, announcement of data and in all professional activities. |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | By carrying out scientific research in their field, graduates evaluate and interpret deeply and broadly, their findings and apply their findings. | |
2) | Graduates have extensive knowledge about current techniques and methods applied in engineering and their limitations. | |
3) | Graduates can complet and implement knowledge using scientific methods using limited or incomplete data; can use the information of different disciplines together. | |
4) | Graduates are aware of new and evolving practices of their profession, examinining new knowledge and learning as necessary | |
5) | Graduates can define and formulate problems related to the field, develop methods to solve them and apply innovative methods in solutions. | |
6) | Graduates develop new and/or original ideas and methods; design complex systems or processes and develop innovative / alternative solutions in their designs. | |
7) | Graduates design and apply theoretical, experimental and model-based research; analyze and investigate the complex problems encountered in this process. | |
8) | Lead in multidisciplinary teams, develop solution approaches in complex situations, work independently and take responsibility. | |
9) | A foreign language communicates verbally and in writing using at least the European Language Portfolio B2 General Level. | |
10) | Transfers the processes and outcomes of their work in a systematic and explicit manner, either written or verbally, in the national or international contexts of that area. | |
11) | Recognize the social, environmental, health, safety, legal aspects of engineering applications, as well as project management and business life practices, and are aware of the limitations they place on engineering applications. | |
12) | Consider social, scientific and ethical values in the collection, interpretation, announcement of data and in all professional activities. |
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 | 15 | 3 | 45 |
Presentations / Seminar | 1 | 30 | 30 |
Project | 1 | 48 | 48 |
Midterms | 1 | 70 | 70 |
Paper Submission | 1 | 12 | 12 |
Final | 1 | 100 | 100 |
Total Workload | 305 |