Stochastic Processes and Markov Chains
MATH-40027
Explore the dynamic world of stochastic processes, where randomness and uncertainty reveal insights into complex phenomena.
This course introduces the fundamentals of probability theory and provides a thorough understanding of Markov chains, with practical applications across diverse fields such as finance, engineering, and biology. Designed for professionals looking to elevate their data analysis skills, students aiming to specialize in stochastic modeling, or anyone intrigued by the interplay of probability and dynamic systems, this course offers both theoretical foundations and real-world applications to bring these concepts to life.
Course Highlights:
- Set Theory and Its Applications to Probability
- Discrete Random Variables
- Continuous Random Variables
- Pairs of Random Variables
- Random Vectors
- Stochastic Processes
- Markov Chains
- Applications in MATLAB
Course Benefits:
- Understand and apply foundational concepts in probability theory, including set theory and its relevance to probability.
- Distinguish between discrete and continuous random variables and analyze their properties and applications.
- Analyze pairs of random variables and random vectors, understanding their interactions within stochastic models.
- Demonstrate proficiency in the basics of stochastic processes, with an emphasis on Markov chains and their theoretical and practical applications.
- Use Markov chains to model and solve real-world problems across different fields using MATLAB to simulate stochastic processes and analyze data for practical insights.
- Integrate stochastic modeling skills to support advanced data analysis and decision-making processes in professional or academic context
Transferring for College Credit
Credit earned in Extended Studies courses may lead to the award of a formal certificate by UC San Diego Division of Extended Studies or be applied toward an academic degree or professional credential, subject to at the approval of the receiving institution(s).
Course Typically Offered: Every quarter. Live discussion sessions will be held once a week. Attendance in these sessions is optional and the sessions will be recorded for students to view later. Exams will be given online during a set date and time.
Prerequisites: Before taking this course, students should have previously taken Calculus I, or an equivalent course.
More information: For more information about this course contact unex-techdata@ucsd.edu.
Course Information
Course sessions
Section ID:
Class type:
This course is entirely web-based and to be completed asynchronously between the published course start and end dates. Synchronous attendance is NOT required.
You will have access to your online course on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.
Textbooks:
All course materials are included unless otherwise stated.
Policies:
- No refunds after: 9/29/2025
Schedule:
Section ID:
Class type:
This course is entirely web-based and to be completed asynchronously between the published course start and end dates. Synchronous attendance is NOT required.
You will have access to your online course on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.
Textbooks:
All course materials are included unless otherwise stated.
Policies:
- No refunds after: 1/19/2026
Schedule:
Instructor:
Jovana Dedeic
As an assistant professor at FTN, Jovana brings a dynamic and engaging approach to teaching, fostering enthusiasm for learning through innovative methods and real-world applications. Over the years, she has taught and assisted in a wide range of courses, including Mathematical Statistics, Calculus I and III, Mathematical Analysis, Operational Research, Formal Models in Distributed Computing, and Automata Theory.
Beyond academia, Jovana is passionate about traveling, fitness, hiking, and reading, embodying a well-rounded approach to life and learning.