SOFTWARE 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	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:	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)	Be able to specify functional and non-functional attributes of software projects, processes and products.
2)	Be able to design software architecture, components, interfaces and subcomponents of a system for complex engineering problems.
3)	Be able to develop a complex software system with in terms of code development, verification, testing and debugging.
4)	Be able to verify software by testing its program behavior through expected results for a complex engineering problem.
5)	Be able to maintain a complex software system due to working environment changes, new user demands and software errors that occur during operation.
6)	Be able to monitor and control changes in the complex software system, to integrate the software with other systems, and to plan and manage new releases systematically.
7)	Be able to identify, evaluate, measure, manage and apply complex software system life cycle processes in software development by working within and interdisciplinary teams.
8)	Be able to use various tools and methods to collect software requirements, design, develop, test and maintain software under realistic constraints and conditions in complex engineering problems.
9)	Be able to define basic quality metrics, apply software life cycle processes, measure software quality, identify quality model characteristics, apply standards and be able to use them to analyze, design, develop, verify and test complex software system.
10)	Be able to gain technical information about other disciplines such as sustainable development that have common boundaries with software engineering such as mathematics, science, computer engineering, industrial engineering, systems engineering, economics, management and be able to create innovative ideas in entrepreneurship activities.
11)	Be able to grasp software engineering culture and concept of ethics and have the basic information of applying them in the software engineering and learn and successfully apply necessary technical skills through professional life.
12)	Be able to write active reports using foreign languages and Turkish, understand written reports, prepare design and production reports, make effective presentations, give clear and understandable instructions.
13)	Be able to have knowledge about the effects of engineering applications on health, environment and security in universal and societal dimensions and the problems of engineering in the era and the legal consequences of engineering solutions.