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Course Detail

Course Detail

Course Description Course Outline Course Contribution to Program Qualifications Assessment Methods ECTS-Workload Detail Informations of the Course Numerical Data

Course Description

Course	Code	Semester	T+P (Hour)	Credit	ECTS
INFORMATION THEORY	EEE4117455	Fall Semester	3+0	3	6

Course Program

Pazartesi 13:30-14:15

Pazartesi 14:30-15:15

Pazartesi 15:30-16:15

Prerequisites Courses
Recommended Elective Courses

Language of Course	English
Course Level	First Cycle (Bachelor's Degree)
Course Type	Elective
Course Coordinator	Assist.Prof. Mustafa TÜRKBOYLARI
Name of Lecturer(s)	Assist.Prof. Mustafa TÜRKBOYLARI
Assistant(s)
Aim	This course introduces the fundamental concepts of Information Theory as established by Claude Shannon. We will explore what information is, how it can be quantified, and the fundamental limits on compressing data (source coding) and reliably transmitting data over noisy communication channels (channel capacity). Topics include entropy, mutual information, Huffman coding, the Asymptotic Equipartition Property (AEP), channel coding theorem, differential entropy, and an introduction to Gaussian channels.
Course Content	This course contains; .

Course Learning Outcomes	Teaching Methods	Assessment Methods

Teaching Methods:
Assessment Methods:

Course Outline

Order	Subjects	Preliminary Work

Resources

Course Contribution to Program Qualifications

Course Contribution to Program Qualifications
No	Program Qualification	Contribution Level
No	Program Qualification	1	2	3	4	5
1	An ability to apply knowledge of mathematics, science, and engineering
2	An ability to identify, formulate, and solve engineering problems
3	An ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability
4	An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice
5	An ability to design and conduct experiments, as well as to analyze and interpret data
6	An ability to function on multidisciplinary teams
7	An ability to communicate effectively
8	A recognition of the need for, and an ability to engage in life-long learning
9	An understanding of professional and ethical responsibility
10	A knowledge of contemporary issues
11	The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context

Assessment Methods

Contribution Level	Absolute Evaluation
Rate of Midterm Exam to Success		30
Rate of Final Exam to Success		70
Total		100

ECTS / Workload Table
Activities				Number of	Duration(Hour)	Total Workload(Hour)
Course Hours				0	0	0
Guided Problem Solving				0	0	0
Resolution of Homework Problems and Submission as a Report				0	0	0
Term Project				0	0	0
Presentation of Project / Seminar				0	0	0
Quiz				0	0	0
Midterm Exam				0	0	0
General Exam				0	0	0
Performance Task, Maintenance Plan				0	0	0
Total Workload(Hour)						0
*Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30=(0/30)**						0
ECTS of the course: 30 hours of work is counted as 1 ECTS credit.

Detail Informations of the Course

Course Description

Course	Code	Semester	T+P (Hour)	Credit	ECTS
INFORMATION THEORY	EEE4117455	Fall Semester	3+0	3	6

Course Program

Pazartesi 13:30-14:15

Pazartesi 14:30-15:15

Pazartesi 15:30-16:15

Prerequisites Courses
Recommended Elective Courses

Language of Course	English
Course Level	First Cycle (Bachelor's Degree)
Course Type	Elective
Course Coordinator	Assist.Prof. Mustafa TÜRKBOYLARI
Name of Lecturer(s)	Assist.Prof. Mustafa TÜRKBOYLARI
Assistant(s)
Aim	This course introduces the fundamental concepts of Information Theory as established by Claude Shannon. We will explore what information is, how it can be quantified, and the fundamental limits on compressing data (source coding) and reliably transmitting data over noisy communication channels (channel capacity). Topics include entropy, mutual information, Huffman coding, the Asymptotic Equipartition Property (AEP), channel coding theorem, differential entropy, and an introduction to Gaussian channels.
Course Content	This course contains; .

Course Learning Outcomes	Teaching Methods	Assessment Methods

Teaching Methods:
Assessment Methods:

Course Outline

Order	Subjects	Preliminary Work

Resources

Course Contribution to Program Qualifications

Course Contribution to Program Qualifications
No	Program Qualification	Contribution Level
No	Program Qualification	1	2	3	4	5
1	An ability to apply knowledge of mathematics, science, and engineering
2	An ability to identify, formulate, and solve engineering problems
3	An ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability
4	An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice
5	An ability to design and conduct experiments, as well as to analyze and interpret data
6	An ability to function on multidisciplinary teams
7	An ability to communicate effectively
8	A recognition of the need for, and an ability to engage in life-long learning
9	An understanding of professional and ethical responsibility
10	A knowledge of contemporary issues
11	The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context

Assessment Methods

Contribution Level	Absolute Evaluation
Rate of Midterm Exam to Success		30
Rate of Final Exam to Success		70
Total		100

Numerical Data

Publication Date: 09/10/2023 - 10:37Last Update Date: 17/06/2026 - 11:46

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