Course overview
In this course, students will develop a sound theoretical understanding of probability and its application to data analytics. Content includes: Axioms of probability; probability distributions; stochastic modelling; model fitting; filtering; linear and matrix algebra, probabilistic modelling of large empirical data such as internet modelling applications.
Course learning outcomes
- Describe the common probability distributions and applications where these distributions occur.
- Develop probabilistic models for large data sets generated by an application.
- Use linear and matrix algebra techniques to manipulate vector data.