Syllabus Application
Stochastic Processes
IE 503
Faculty:
Faculty of Engineering and Natural Sciences
Semester:
Fall 2025-2026
Course:
Stochastic Processes - IE 503
Classroom:
FENS-G029
Level of course:
Masters
Course Credits:
SU Credit:3.000, ECTS:10
Prerequisites:
-
Corequisites:
-
Course Type:
Lecture
Instructor(s) Information
Ahmet Barış Balcıoğlu
- Email: balcioglu@sabanciuniv.edu
Course Information
Catalog Course Description
Introduction to probability theory; random variables; conditional probability and conditional expectation; Poisson and renewal processes; discrete and continuous Markov chains; applications in queuing, reliability, inventory, production, and telecommunication problems.
Course Learning Outcomes:
| 1. | The student will be able to model stochastic phenomena in real life (when it applies) as a discrete time or a continuous time Markov chain. |
|---|---|
| 2. | The student will be able to analyze, present, and criticize academic papers involving stochastic processes, queueing models, Markov chains. |
| 3. | The student will link how the probability theory can be employed to model and analyze systems that evolve randomly over time. |
| 4. | The student will learn how a customer arrival process can be modeled as a Poisson process. |
Course Objective
In this course, we will review the fundamental concepts of the theory of probability and learn about a variety of stochastic processes and we will also discuss some of their applications in engineering. The main objective of this course is to enable students to think probabilistically and to develop and analyze probability models that capture the effects of randomness on systems under consideration.