Akademik Dersler - Tanıtım


Code - Course Title	BİL539 - Artificial Intelligence
Course Type	Required Courses
Language of Instruction	İngilizce
Laboratory + Practice	3+0
ECTS	7.5
Course Instructor(s)	DOKTOR ÖĞRETİM ÜYESİ BURCU YILMAZEL
Mode of Delivery	The mode of delivery of this course is Face to face.
Prerequisites	There is no prerequisite or co-requisite for this course.
Courses Recomended	None.
Required or Recommended Resources	Russell, S. J. & Norvig, P. Artificial Intelligence: A Modern Approach. 4. baskı. Pearson, 2020.
Recommended Reading List	Goodfellow, I., Bengio, Y. & Courville, A. Deep Learning. MIT Press, 2016. Reddi, V. J. ve ark. Machine Learning Systems: Principles and Practices of Engineering Artificially Intelligent Systems. mlsysbook.ai.
Assessment methods and criteria	Midterm Exam, Homework, and Final.
Work Placement	None.
Sustainability Development Goals	Quality Education , Industry, Innovation and Infrastructure

Weeks	Topics
Week - 1	Introduction to artificial intelligence and intelligent agents
Week - 2	Problem solving: Uninformed and informed (heuristic) search methods
Week - 3	Local search, adversarial search, and game-theoretic approaches
Week - 4	Constraint satisfaction problems and symbolic reasoning
Week - 5	Knowledge representation, knowledge-based agents, and logical inference
Week - 6	Foundations of machine learning
Week - 7	Foundations of machine learning
Week - 8	Deep learning and representation learning approaches
Week - 9	Reinforcement learning
Week - 10	AI applications
Week - 11	AI applications
Week - 12	AI applications
Week - 13	Ethics, trustworthiness, and social responsibility in artificial intelligence
Week - 14	Current research directions and future perspectives in artificial intelligence

Assessment Method and Passing Requirements
	Quamtity	Percentage (%)
1.Midterm Exam	1	35
Homework	1	25
Final Exam	1	40
Toplam (%)		100