Akademik Dersler - Tanıtım


Code - Course Title	İST557 - Explainable Artificial Intelligence
Course Type	Elective Courses
Language of Instruction	Türkçe
Laboratory + Practice	3+0
ECTS	7.5
Course Instructor(s)	DOÇENT DOKTOR MUSTAFA ÇAVUŞ
Mode of Delivery	This course will only face-to-face training.
Prerequisites	There is no prerequisite or co-requisite for this course.
Courses Recomended	There are no suggested lessons related with this course.
Required or Recommended Resources	Biecek and Burzykowski (2021) Explanatory Model Analysis, https://ema.drwhy.ai.Molnar (2022) Interpretable Machine Learning, https://christophm.github.io/interpretable-ml-book/
Recommended Reading List
Assessment methods and criteria	2 Interim reports and 1 Final Report
Work Placement	This is not appropriate for the course.
Sustainability Development Goals

Weeks	Topics
Week - 1	Introduction to Explainable Artificial Intelligence
Week - 2	Local and Global Level Explainers
Week - 3	Break-Down Method
Week - 4	Shapley Values
Week - 5	LIME Method
Week - 6	Ceteris-Paribus Profiles
Week - 7	Variable Importance Measures
Week - 8	Partial-Dependence Profiles
Week - 9	Accumulated Local Effect Profiles
Week - 10	Model Performance Measures
Week - 11	Counterfactual Explanations
Week - 12	Reporting of Model Behavior
Week - 13	Project Presentations
Week - 14	Project Presentations

Assessment Method and Passing Requirements
	Quamtity	Percentage (%)
Homework	1	50
Final Exam	1	50
Toplam (%)		100