PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
BMM 534	MACHINE LEARNING AND APPLİCATİONS	3 + 0	2nd Semester	7,5

COURSE DESCRIPTION

Course Level	Doctorate Degree
Course Type	Elective
Course Objective	This course aims at providing a theoretical basis for machine learning and its use with examples of biomedical applications.
Course Content	Introduction to machine learning, multi-variable models and regression, supervised learning, bayesian learning, model selection, artificial neural networks, nearest neighbor, support vector machines, decision trees, unsupervised learning, reinforcement learning
Prerequisites	No the prerequisite of lesson.
Corequisite	No the corequisite of lesson.
Mode of Delivery	Face to Face

COURSE LEARNING OUTCOMES

1	Knows fundamental concepts about machine learning
2	Knows machine learning structures
3	Can solve real-world problem by using machine learning methods

COURSE'S CONTRIBUTION TO PROGRAM

Data not found.

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)	14	3	42
Mid-terms	1	56	56
Final examination	1	56	56
Special Study Module (Student)	1	41	41
Total Work Load ECTS Credit of the Course			195 7,5

COURSE DETAILS

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L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes

Prospective Student