COURSE INTRODUCTION AND APPLICATION INFORMATION

se.cs.ieu.edu.tr

Course Name

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
	Fall/Spring

Prerequisites

ISE 305

To succeed (To get a grade of at least DD)

Course Language

Course Type

Elective

Course Level

Mode of Delivery

Teaching Methods and Techniques of the Course

Course Coordinator

Course Lecturer(s)

Assistant(s)

Course Objectives
Learning Outcomes	The students who succeeded in this course; Will be able to be acquainted with the basic stochastic processes that are widely used in operations research and industrial engineering Will be able to understand basic structure of various stochastic processes Will be able to understand various techniques used to analyze stochastic processes Will be able to use stochastic processes to explain random phenomenon Will be able to develop stochastic models in various contexts
Course Description

Course Category	Core Courses
	Major Area Courses
	Supportive Courses
	Media and Managment Skills Courses
	Transferable Skill Courses

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week	Subjects	Required Materials
1	Probability Review	Ch 1 HM. Taylor, S. Karlin, An Introduction to Stochastic Modeling, Wiley, 1998.
2	Conditional Probability and Conditional Expectation	Ch 2 HM. Taylor, S. Karlin, An Introduction to Stochastic Modeling, Wiley, 1998.
3	Conditional Probability and Conditional Expectation	Ch 2 HM. Taylor, S. Karlin, An Introduction to Stochastic Modeling, Wiley, 1998.
4	Markov Chains	Ch 3 HM. Taylor, S. Karlin, An Introduction to Stochastic Modeling, Wiley, 1998.
5	Markov Chains	Ch 3 HM. Taylor, S. Karlin, An Introduction to Stochastic Modeling, Wiley, 1998.
6	LongRun Behavior of Markov Chains	Ch 4 HM. Taylor, S. Karlin, An Introduction to Stochastic Modeling, Wiley, 1998.
7	Review and Midterm Exam
8	LongRun Behavior of Markov Chains	Ch 4 HM. Taylor, S. Karlin, An Introduction to Stochastic Modeling, Wiley, 1998.
9	Poisson Processes	Ch 5 HM. Taylor, S. Karlin, An Introduction to Stochastic Modeling, Wiley, 1998.
10	Poisson Processes	Ch 5 HM. Taylor, S. Karlin, An Introduction to Stochastic Modeling, Wiley, 1998.
11	ContinuousTime Markov Chains	Ch 6 HM. Taylor, S. Karlin, An Introduction to Stochastic Modeling, Wiley, 1998.
12	ContinuousTime Markov Chains	Ch 6 HM. Taylor, S. Karlin, An Introduction to Stochastic Modeling, Wiley, 1998.
13	Renewal Phenomena	Ch 7 HM. Taylor, S. Karlin, An Introduction to Stochastic Modeling, Wiley, 1998.
14	Renewal Phenomena	Ch 7 HM. Taylor, S. Karlin, An Introduction to Stochastic Modeling, Wiley, 1998.
15	General review and evaluation
16	Review of the Semester

Course Notes/Textbooks	HM. Taylor, S. Karlin, An Introduction to Stochastic Modeling, Wiley, 1998.
Suggested Readings/Materials

EVALUATION SYSTEM

Semester Activities	Number	Weigthing
Participation	1	10
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	3	10
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterm	1	40
Final Exam	1	40
Total

Weighting of Semester Activities on the Final Grade		60
Weighting of End-of-Semester Activities on the Final Grade		40
Total

ECTS / WORKLOAD TABLE

Semester Activities	Number	Duration (Hours)	Workload
Course Hours (Including exam week: 16 x total hours)	16	3	48
Laboratory / Application Hours (Including exam week: 16 x total hours)	16
Study Hours Out of Class	15	2
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	3	7
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterms	1	8
Final Exams	1	13
		Total	120

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#	Program Competencies/Outcomes	* Contribution Level
#	Program Competencies/Outcomes	1	2	3	4	5
1	Be able to define problems in real life by identifying functional and nonfunctional requirements that the software is to execute
2	Be able to design and analyze software at component, subsystem, and software architecture level
3	Be able to develop software by coding, verifying, doing unit testing and debugging
4	Be able to verify software by testing its behaviour, execution conditions, and expected results
5	Be able to maintain software due to working environment changes, new user demands and the emergence of software errors that occur during operation
6	Be able to monitor and control changes in the software, the integration of software with other software systems, and plan to release software versions systematically
7	To have knowledge in the area of software requirements understanding, process planning, output specification, resource planning, risk management and quality planning
8	Be able to identify, evaluate, measure and manage changes in software development by applying software engineering processes
9	Be able to use various tools and methods to do the software requirements, design, development, testing and maintenance
10	To have knowledge of basic quality metrics, software life cycle processes, software quality, quality model characteristics, and be able to use them to develop, verify and test software
11	To have knowledge in other disciplines that have common boundaries with software engineering such as computer engineering, management, mathematics, project management, quality management, software ergonomics and systems engineering		X
12	Be able to grasp software engineering culture and concept of ethics, and have the basic information of applying them in the software engineering
13	Be able to use a foreign language to follow related field publications and communicate with colleagues				X

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest