Statistical Machine Learning & Data Analytics
Supervised and unsupervised learning methods for prediction and insight from data.
Stochastic Processes Modelling
Markov chains, Poisson processes and Brownian motion with actuarial and financial applications.
Advanced 6 topics 12 months access Online reader
About this course
The language of randomness over time. The course develops Markov chains, counting processes, continuous-time Markov models and Brownian motion, and shows how they model insurance claims, health states, epidemics and asset prices.
What you will learn
- Classify stochastic processes and their properties
- Analyse discrete- and continuous-time Markov chains
- Model claim arrivals with Poisson and counting processes
- Use Brownian motion and simple stochastic calculus in finance
Course topics
- Principles of stochastic processes
- Discrete-time Markov chains
- Poisson and counting processes
- Continuous-time Markov models
- Brownian motion
- Applications in insurance, health and finance
Who this course is for
- Actuarial science and statistics students
- Candidates preparing for stochastic-modelling examinations
- Researchers modelling risk, health or epidemics
Before you start
Probability theory and calculus.
How access works
After payment, the course materials appear in My Learning. They open in a secure online reader on your phone, tablet or computer for 12 months. Materials are view-only and cannot be downloaded. Buying again extends your access from the current end date.
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