| Code - Course Title |
YZM2004 - Principles of Artificial Intelligence |
| Course Type |
Required Courses |
| Language of Instruction |
İngilizce |
| Laboratory + Practice |
3+1 |
| ECTS |
5.0 |
| Course Instructor(s) |
DOKTOR ÖĞRETİM ÜYESİ NİHAL İNCE |
| Mode of Delivery |
This course is offered exclusively in an in-person format. |
| Prerequisites |
There are no prerequisites or co-requisites for this course. |
| Courses Recomended |
There are no other recommended courses related to this one. |
| Required or Recommended Resources |
Russell, S., & Norvig, P. (2020). Artificial intelligence: A modern approach (4th ed.). Pearson.Poole, D. L., & Mackworth, A. K. (2023). Artificial intelligence: Foundations of computational agents (3rd ed.). Cambridge University Press.Kopec, D. (2019). Classic computer science problems in Python. Manning Publications.Koller, D., & Friedman, N. (2009). Probabilistic graphical models: Principles and techniques. MIT Press.James, G., Witten, D., Hastie, T., & Tibshirani, R. (2021). An introduction to statistical learning: With applications in R/Python. Springer. |
| Recommended Reading List |
Russell, S., & Norvig, P. (2020). Artificial intelligence: A modern approach (4th ed.). Pearson.Poole, D. L., & Mackworth, A. K. (2023). Artificial intelligence: Foundations of computational agents (3rd ed.). Cambridge University Press.Kopec, D. (2019). Classic computer science problems in Python. Manning Publications.Koller, D., & Friedman, N. (2009). Probabilistic graphical models: Principles and techniques. MIT Press.James, G., Witten, D., Hastie, T., & Tibshirani, R. (2021). An introduction to statistical learning: With applications in R/Python. Springer. |
| Assessment methods and criteria |
2 midterm exams, 1 final exam |
| Work Placement |
This is not suitable for this class. |
| Sustainability Development Goals |
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