OS3307 Modeling Practices for Computing

An applied course in modeling and understanding systems where randomness plays a significant role. Topics include basic probability and statistics, queuing models, Monte Carlo and discrete-event simulation, least squares curve fitting, and elements of statistical design of experiments. The focus will be on applications of these techniques in a computer science context.


Discrete Math, Intro Programming

Lecture Hours


Lab Hours


Course Learning Outcomes

  • Recognize basic principles of probability and how to apply them in a computer science context
  • Demonstrate knowledge of techniques commonly used in statistical inference
  • Understand the relationship between probability and statistics, and how it governs good scientific practice in data analysis
  • Develop skills in applying simulation, design of experiments, and queuing models to solve problems in a computer science context