COMPUTER ENGINEERING (ENGLISH, NON-THESIS)
Master	TR-NQF-HE: Level 7	QF-EHEA: Second Cycle	EQF-LLL: Level 7

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
INE5206	Decision Analysis	Fall Spring	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:	Departmental Elective
Course Level:
Mode of Delivery:	Face to face
Course Coordinator :
Recommended Optional Program Components:	N.A.
Course Objectives:	The aim of the course is to introduce the graphical models used in decision analysis and to provide a set of systematic tools to help the decision maker in giving a decision.

Learning Outcomes

The students who have succeeded in this course;
- Recognize the graphical models used in decision analysis.
- Model a given uncertain situation with Bayes networks.
- Compute exact and approximate inferences in Bayes networks.
- Model a given uncertain decision problem with influence diagrams.
- Make inferences in decision networks.
- Compute value of information.

Course Content

Expected Utility, Causal and Bayesian networks, Exact inference in Bayesian networks, Approximate inference in Bayesian networks, Learning Bayesian networks, Influence and decision networks, Value of information

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Probability review
2)	Expected Utility
3)	Causal and Bayesian networks
4)	Building Bayesian models
5)	Exact inference in Bayesian networks
6)	Exact inference in Bayesian networks
7)	Approximate inference in Bayesian networks
8)	Approximate inference in Bayesian networks
9)	Midterm
10)	Learning Bayesian networks
11)	Influence and decision networks
12)	Influence and decision networks
13)	Value of information
14)	Project presentations

Sources

Course Notes / Textbooks:	F.V. Jensen, 2001. Bayesian networks and decision graphs, New York : Springer
References:	Robert T. Clemen, 1996. Making Hard Decisions: An Introduction to Decision Analysis, 2nd edition, Duxbury Press

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Homework Assignments	4	% 10
Project	1	% 20
Midterms	1	% 30
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Workload
Course Hours	14	42
Study Hours Out of Class	14	28
Presentations / Seminar	1	10
Project	4	40
Homework Assignments	4	40
Midterms	1	15
Final	1	20
Total Workload		195

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)	Define and manipulate advanced concepts of Computer Engineering
2)	Use math, science, and modern engineering tools to formulate and solve advenced engineering problems
3)	Notice, detect, formulate and solve new engineering problems.
4)	Review the literature critically pertaining to his/her research projects, and connect the earlier literature to his/her own results
5)	Follow, interpret and analyze scientific researches in the field of engineering and use the knowledge in his/her field of study
6)	Work effectively in multi-disciplinary research teams
7)	Acquire scientific knowledge
8)	Find out new methods to improve his/her knowledge.
9)	Effectively express his/her research ideas and findings both orally and in writing
10)	Defend research outcomes at seminars and conferences.
11)	Prepare master thesis and articles about thesis subject clearly on the basis of published documents, thesis, etc.
12)	Demonstrate professional and ethical responsibility.
13)	Develop awareness for new professional applications and ability to interpret them.