Information Package / Course Catalogue
| Course Code | : EFS177 |
| Course Type | : Non Departmental Elective |
| Couse Group | : First Cycle (Bachelor's Degree) |
| Education Language | : Turkish |
| Work Placement | : N/A |
| Theory | : 2 |
| Prt. | : 0 |
| Credit | : 2 |
| Lab | : 0 |
| ECTS | : 3 |
Having a foundational knowledge of artificial intelligence and being able to use AI effectively and efficiently.
Definition and fundamentals of artificial intelligence, its current position and importance, machine learning, deep learning, and neural networks; natural language processing (NLP) and image processing; AI literacy; prompt engineering; content creation with AI; the future of AI; its use in various disciplines (healthcare, art, engineering, etc.).
| Lec. Ayşe YILMAZ |
| Lec. Fulya TORUN |
| 1. | Explains the fundamental concepts and working principles of artificial intelligence |
| 2. | Evaluates the current position and societal importance of artificial intelligence |
| 3. | Explains the technical infrastructure of artificial intelligence at a basic level |
| 4. | Develops a critical perspective on the effects of artificial intelligence on individuals and society |
| 5. | Compares the features of various AI tools for different purposes. |
| 6. | Predicts possible future developments of artificial intelligence and develops a critical perspective |
| 7. | Predicts the possible future developments of artificial intelligence |
| 8. | Analyzes the applications of artificial intelligence in various disciplines |
| 1. | Goksel, N., & Bozkurt, A. (2019). Artificial intelligence in education: Current insights and future perspectives. In Handbook of Research on Learning in the Age of Transhumanism (pp. 224-236). IGI Global. |
| 2. | Gates, B. (2023). The Age of AI has begun. Gates Notes. https://www.gatesnotes.com/The-Age-of-AI- Has-Begun |
| 3. | Chen, B., Zhang, Z., Langrené, N., & Zhu, S. (2023). Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review. arXiv. DOI: https://doi.org/10.48550/ arXiv.2310.14735 |
| 4. | Dang, H., Mecke, L., Lehmann, F., Goller, S., & Buschek, D. (2022). How to prompt? Opportunities and challenges of zero-and few-shot learning for human-AI interaction in creative applications of generative models. arXiv. DOI: https://doi.org/10.48550/arXiv.2209.01390 |
| Type of Assessment | Count | Percent |
|---|---|---|
| Midterm Examination | 1 | %40 |
| Final Examination | 1 | %60 |
| Activities | Count | Preparation | Time | Total Work Load (hours) |
|---|---|---|---|---|
| Lecture - Theory | 14 | 1 | 2 | 42 |
| Individual Work | 5 | 1 | 1 | 10 |
| Midterm Examination | 1 | 10 | 1 | 11 |
| Final Examination | 1 | 10 | 1 | 11 |
| TOTAL WORKLOAD (hours) | 74 | |||
PÇ-1 | PÇ-2 | PÇ-3 | PÇ-4 | PÇ-5 | PÇ-6 | PÇ-7 | PÇ-8 | PÇ-9 | PÇ-10 | |
OÇ-1 | 5 | 3 | 5 | 5 | 4 | |||||
OÇ-2 | 5 | 3 | 5 | 5 | 4 | |||||
OÇ-3 | 5 | 3 | 4 | 5 | 4 | |||||
OÇ-4 | 5 | 3 | 4 | 5 | 4 | |||||
OÇ-5 | 5 | 3 | 2 | 5 | 4 | |||||
OÇ-6 | 5 | 3 | 4 | 5 | 4 | |||||
OÇ-7 | 5 | 3 | 4 | 5 | 4 | |||||
OÇ-8 | 5 | 3 | 4 | 5 | 4 | |||||