PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
BMM 677	DEEP LEARNING APPLICATIONS IN MEDICAL DATA	3 + 0	1st Semester	7,5

COURSE DESCRIPTION

Course Level	Master's Degree
Course Type	Elective
Course Objective	The aim of this course is to learn the basic concepts and model architectures of deep learning, which is an artificial intelligence method, and to perform applications in medical data with MATLAB and Python programs.
Course Content	Basic concepts, Introduction to Machine Learning, Artificial Neural Networks, Deep learning concepts, Hyperparameters, Optimization and Regularization, Convolutional Neural Networks, Deep learning architectures, Classification and prediction in medical data, Use of deep learning in medical data, Matlab and Python deep learning libraries, Matlab and medical data classification, prediction, and object detection using Python deep learning libraries
Prerequisites	No the prerequisite of lesson.
Corequisite	No the corequisite of lesson.
Mode of Delivery	Face to Face

COURSE LEARNING OUTCOMES

1	To learn the fundamentals of deep learning
2	To be able to describe the basic model architectures of deep learning
3	To be able to use deep learning methods in medical data
4	To be able to develop software that can analyze medical data using deep learning libraries in MATLAB and Python languages.

COURSE'S CONTRIBUTION TO PROGRAM

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

Select Year

	Course Term	No	Instructors
Details	2022-2023 Spring	1	MUHAMMET ÜSAME ÖZİÇ

Course Details

Course Code	Course Title	L+P Hour	Course Code	Language Of Instruction	Course Semester
BMM 677	DEEP LEARNING APPLICATIONS IN MEDICAL DATA	3 + 0	1	Turkish	2022-2023 Spring

Course Coordinator	E-Mail	Phone Number	Course Location	Attendance
Asts. Prof. Dr. MUHAMMET ÜSAME ÖZİÇ	muozic@pau.edu.tr		TEK A0402-22	%

Goals		The aim of this course is to learn the basic concepts and model architectures of deep learning, which is an artificial intelligence method, and to perform applications in medical data with MATLAB and Python programs.
Content		Basic concepts, Introduction to Machine Learning, Artificial Neural Networks, Deep learning concepts, Hyperparameters, Optimization and Regularization, Convolutional Neural Networks, Deep learning architectures, Classification and prediction in medical data, Use of deep learning in medical data, Matlab and Python deep learning libraries, Matlab and medical data classification, prediction, and object detection using Python deep learning libraries

Topics

Weeks	Topics
1	Basic Concepts
2	Machine Learning
3	Image Processing Fundamentals
4	Artificial neural networks
5	Application Platforms and Package Programs
6	Artificial Neural Networks Parameters
7	Artificial Neural Networks Applications
8	Deep Learning
9	Convolutional Neural Networks
10	Hyperparameters
11	Semantic Segmentation Algorithms
12	Object Detection Algorithms
13	Application in Medical Data-1
14	Application in Medical Data-2

Materials

Materials are not specified.

Resources

Resources	Resources Language
	Türkçe
Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications, Om Preakash, Brahat Bhushan, Utku Köse, CRC Press	Türkçe

Course Assessment

Assesment Methods	Percentage (%)	Assesment Methods Title
Final Exam	50	Final Exam
Midterm Exam	50	Midterm Exam

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

Prospective Student