COURSE INTRODUCTION AND APPLICATION INFORMATION

ce.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	X
	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	Adequate knowledge in Mathematics, Science and Computer Engineering; ability to use theoretical and applied information in these areas to model and solve Computer Engineering problems				X
2	Ability to identify, define, formulate, and solve complex Computer Engineering problems; ability to select and apply proper analysis and modeling methods for this purpose				X
3	Ability to design a complex computer based system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose				X
4	Ability to devise, select, and use modern techniques and tools needed for Computer Engineering practice				X
5	Ability to design and conduct experiments, gather data, analyze and interpret results for investigating Computer Engineering problems				X
6	Ability to work efficiently in Computer Engineering disciplinary and multi-disciplinary teams; ability to work individually
7	Ability to communicate effectively in Turkish, both orally and in writing; knowledge of a minimum of two foreign languages
8	Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself
9	Awareness of professional and ethical responsibility
10	Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development
11	Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of Computer Engineering solutions

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