ENERGY SYSTEMS ENGINEERING
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
EEE5600	Introduction to Information and Coding Theory	Fall	3	0	3	12

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:
Course Coordinator :	Assoc. Prof. SAEID KARAMZADEH
Course Lecturer(s):	Assoc. Prof. ALKAN SOYSAL
Recommended Optional Program Components:	none..........
Course Objectives:	The aim of this course is to understand, in detail, basic information theory and coding theory arguments. Information theoretic analysis covers entropy/mutual information, source and channel coding. Coding theory analysis covers code construction, linear codes, cyclic and convolutional codes, near capacity codes.

Learning Outcomes

The students who have succeeded in this course;
1. Understand basic concepts and definitions of information theory
2. Know and apply source and channel coding theorems
3. Gain knowledge on code constructions
4. Understand basic concepts of coding theory
5. Apply modern error correcting codes

Course Content

This course covers basics of information theory and coding theory. The course starts with definitions of information theoretic quantities such as entropy, mutual information, etc. It covers Shannon's source coding theorem and explains Shannon codes and Huffman codes. Then Shannon's channel coding theorem is analyzed and capacity values of several channels are calculated. In the second half of the course, basic code construction methods are explained. Linear codes, cyclic codes, convolutional codes are introduced.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction to basic concepts of information transfer
2)	Define concepts of entropy, relative entropy, conditional entropy
3)	Definition of mutual information and its calculation for different scenarios.
4)	Source coding theorem
5)	Applications of source coding theorem: Shannon codes, Huffman codes
6)	Channel coding theorem
7)	Differential entropy
8)	Capacity calculations for different channel models. Midterm
9)	The Gaussian channel and its capacity
10)	Basics of code construction, Error detection and correction
11)	Linear block codes
12)	Cyclic codes
13)	Convolutional codes
14)	Near capacity codes

Sources

Course Notes / Textbooks:	Thomas and Cover, "Elements of Information Theory", 2nd Edition, Wiley.
References:	none..........

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Project	1	% 30
Midterms	1	% 30
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 30
PERCENTAGE OF FINAL WORK		% 70
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Workload
Course Hours	14	42
Project	4	50
Midterms	8	60
Final	4	48
Total Workload		200

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Build up a body of knowledge in mathematics, science and Energy Systems Engineering subjects; use theoretical and applied information in these areas to model and solve complex engineering problems.
2)	Ability to identify, formulate, and solve complex Energy Systems Engineering problems; select and apply proper modeling and analysis methods for this purpose.
3)	Ability to design complex Energy systems, processes, devices or products under realistic constraints and conditions, in such a way as to meet the desired result; apply modern design methods for this purpose.
4)	Ability to devise, select, and use modern techniques and tools needed for solving complex problems in Energy Systems Engineering practice; employ information technologies effectively.
5)	Ability to design and conduct numerical or pysical experiments, collect data, analyze and interpret results for investigating the complex problems specific to Energy Systems Engineering.
6)	Ability to cooperate efficiently in intra-disciplinary and multi-disciplinary teams; and show self-reliance when working on Energy Systems-related problems
7)	Ability to communicate effectively in English and Turkish (if he/she is a Turkish citizen), both orally and in writing. Write and understand reports, prepare design and production reports, deliver effective presentations, give and receive clear and understandable instructions.
8)	Recognize the need for life-long learning; show ability to access information, to follow developments in science and technology, and to continuously educate oneself.
9)	Develop an awareness of professional and ethical responsibility, and behave accordingly. Be informed about the standards used in Energy Systems Engineering applications.
10)	Learn about business life practices such as project management, risk management, and change management; develop an awareness of entrepreneurship, innovation, and sustainable development.
11)	Acquire knowledge about the effects of practices of Energys Systems Engineering on health, environment, security in universal and social scope, and the contemporary problems of Energys Systems engineering; is aware of the legal consequences of Energys Systems engineering solutions.