Istanbul Health and Technology University INFORMATION PACKAGE / COURSE CATALOGUE
| Mechatronics Engineering | |||||
| Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 | ||
Course General Introduction Information
| Course Code: | BYM308 | ||||
| Course Name: | Introduction to Artificial Intelligence | ||||
| Course Semester: | Spring | ||||
| Course Credits: |
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| Language of instruction: | TR | ||||
| Course Requirement: | |||||
| Does the Course Require Work Experience?: | No | ||||
| Type of course: | Departmental Elective | ||||
| Course Level: |
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| Mode of Delivery: | Face to face | ||||
| Course Coordinator : | Assoc. Prof. HATİCE ESRA ÖZKAN UÇAR | ||||
| Course Lecturer(s): | Prof. Dr. Halis ALTUN | ||||
| Course Assistants: |
Course Purpose and Content
| Course Objectives: | The aim of this course is to provide students the knowledge about the basic techniques and methodologies of artificial intelligence and abilities to apply artificial intelligence methods on practical problems. |
| Course Content: | Basic concepts and techniques of AI. Problem solving in AI, informed and uninformed search techniques, Local search techniques and simulated annealing. Meta-heuristic search methods. Introduction to Neural Networks. Game playing, Prolog overview, knowledge representation and reasoning. |
Learning Outcomes
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The students who have succeeded in this course;
1) Knowledge about the basic methodologies in artificial intelligence., 2) Ability to use knowledge to formulate, and solve practical problems using artificial intelligence techniques. |
Course Flow Plan
| Week | Subject | Related Preparation |
| 1) | Introductory terms, foundations, history and philosophy of AI | - |
| 2) | Intelligent Agents | - |
| 3) | Problem Solving and Introduction to Search Methods | - |
| 4) | Uninformed Search Methodologies | - |
| 5) | Heuristic Search | - |
| 6) | Game Playing | - |
| 7) | Meta-Heuristics | - |
| 8) | Neural Networks | - |
| 9) | Knowledge Based Agents | - |
| 10) | First Order Logic | - |
| 11) | Inference in First Order Logic | - |
| 12) | Prolog and Logic Programming | - |
| 13) | Prolog and Logic Programming | - |
| 14) | Probabilistic Reasoning | - |
Sources
| Course Notes / Textbooks: | Artificial Intelligence: A Modern Approach. Stuart Russell, Peter Norvig, Prentice Hall, Second Edition. |
| References: | Artificial Intelligence: A Modern Approach. Stuart Russell, Peter Norvig, Prentice Hall, Second Edition. |
Course - Learning Outcome Relationship
| No Effect | 1 Lowest | 2 Medium | 3 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | 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. | |
| 2) | Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modelling methods for this purpose. | |
| 3) | 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. | |
| 4) | 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. | |
| 5) | Ability to design and conduct experiments, gather data, analyse and interpret results for investigating complex engineering problems or discipline specific research questions. | |
| 6) | Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. | |
| 7) | 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. | |
| 8) | 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. | |
| 9) | Consciousness to behave according to ethical principles and professional and ethical responsibility; knowledge on standards used in engineering practice. | |
| 10) | Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development. | |
| 11) | 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 |
Learning Activity and Teaching Methods
| Alan Çalışması | |
| Anlatım | |
| Beyin fırtınası /Altı şapka | |
| Bireysel çalışma ve ödevi | |
| Course | |
| Grup çalışması ve ödevi | |
| Labs | |
| Homework | |
| Problem Çözme | |
| Uygulama (Modelleme, Tasarım, Maket, Simülasyon, Deney vs.) |
Measurement and Evaluation Methods and Criteria
| Yazılı Sınav (Açık uçlu sorular, çoktan seçmeli, doğru yanlış, eşleştirme, boşluk doldurma, sıralama) | |
| Sözlü sınav | |
| Homework | |
| Uygulama | |
| Bireysel Proje | |
| Grup Projesi | |
| Sunum |
Assessment & Grading
| Semester Requirements | Number of Activities | Level of Contribution |
| Application | 2 | % 30 |
| Midterms | 1 | % 30 |
| Final | 1 | % 40 |
| total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 60 | |
| PERCENTAGE OF FINAL WORK | % 40 | |
| total | % 100 | |
İş Yükü ve AKTS Kredisi Hesaplaması
| Activities | Number of Activities | Aktiviteye Hazırlık | Aktivitede Harçanan Süre | Aktivite Gereksinimi İçin Süre | Workload | ||
| Course Hours | 10 | 5 | 50 | ||||
| Application | 3 | 9 | 27 | ||||
| Homework Assignments | 2 | 24 | 48 | ||||
| Midterms | 1 | 24 | 24 | ||||
| Final | 1 | 24 | 24 | ||||
| Total Workload | 173 | ||||||