Akademik Dersler - Tanıtım


Code - Course Title	BİM453 - Introduction to Machine Learning
Course Type	Area Elective Courses
Language of Instruction	İngilizce
Laboratory + Practice	3+0
ECTS	4.5
Course Instructor(s)	PROFESÖR DOKTOR SERKAN GÜNAL
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	Linear Algebra, Probability and Statistics.
Required or Recommended Resources	Géron, Aurélien. Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow. OReilly Media Inc., 2022.
Recommended Reading List	Ethem Apaydin, Introduction to Machine Learning, 2e. The MIT Press, 2010.
Assessment methods and criteria	Midterm Exam, Homeworks, Final Exam.
Work Placement	None.
Sustainability Development Goals	Quality Education , Industry, Innovation and Infrastructure

Weeks	Topics
Week - 1	EN: The Machine Learning Landscape
Week - 2	End-to-End Machine Learning Project
Week - 3	End-to-End Machine Learning Project
Week - 4	Classification
Week - 5	Training Models
Week - 6	Training Models
Week - 7	Support Vector Machines
Week - 8	Decision Trees
Week - 9	Ensemble Learning and Random Forests
Week - 10	Ensemble Learning and Random Forests
Week - 11	Dimensionality Reduction
Week - 12	Dimensionality Reduction
Week - 13	Unsupervised Learning
Week - 14	Unsupervised Learning

Assessment Method and Passing Requirements
	Quamtity	Percentage (%)
1.Midterm Exam	1	30
Homework	1	30
Final Exam	1	40
Toplam (%)		100