INDUSTRIAL 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
ISM5206	Decision Analysis	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:	Turkish
Type of course:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Instructor ÖZLEM KANGA
Course Lecturer(s):	Assoc. Prof. SEROL BULKAN
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 exam
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	Duration (Hours)	Workload
Course Hours	14	3	42
Study Hours Out of Class	14	2	28
Presentations / Seminar	1	10	10
Project	1	40	40
Homework Assignments	4	10	40
Midterms	1	15	15
Final	1	20	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)	Build up a body of knowledge in mathematics, science and industrial engineering subjects; use theoretical and applied information in these areas to model and solve complex engineering problems.
2)	Identify, formulate, and solve complex engineering problems; select and apply proper analysis and modeling methods for this purpose.
3)	Design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; apply modern design methods for this purpose. The ability to apply modern design methods to meet this objective.
4)	Devise, select, and use modern techniques and tools needed for solving complex problems in industrial engineering practice; employ information technologies effectively.
5)	Design and conduct experiments, collect data, analyze and interpret results for investigating the complex problems specific to industrial engineering.
6)	Cooperate efficiently in intra-disciplinary and multi-disciplinary teams; and show self-reliance when working independently.
7)	Demonstrate effective communication skills in both oral and written English and Turkish. Writing and understanding reports, preparing design and production reports, making effective presentations, giving and receiving clear and understandable instructions.
8)	Recognize the need for lifelong learning; show ability to access information, to follow developments in science and technology, and to continuously educate him/herself.
9)	Develop an awareness of professional and ethical responsibility, and behaving accordingly. Information about the standards used in engineering applications.
10)	Know business life practices such as project management, risk management, and change management; develop an awareness of entrepreneurship, innovation, and sustainable development.
11)	Know contemporary issues and the global and societal effects of modern age engineering practices on health, environment, and safety; recognize the legal consequences of engineering solutions.
12)	Develop effective and efficient managerial skills.