Markov Chain Course
Dive into Markov chains using real-world engagement data to build transition matrices, examine short- and long-term behaviours, simulate interventions, and deliver clear, data-driven recommendations for impactful decisions. Gain hands-on experience in stochastic modelling to transform uncertainty into strategic advantages, equipping you with tools for precise forecasting and policy evaluation in dynamic systems.

flexible workload of 4 to 360h
valid certificate in your country
What will I learn?
This course provides a practical guide to using Markov chains for analysing weekly engagement data. Participants will learn data cleaning and exploration techniques, transition matrix estimation, analysis of short-term and long-term patterns, and calculation of stationary distributions. Key skills include testing model assumptions, simulating interventions, comparing different scenarios, and producing reproducible reports with actionable insights and uncertainty measures.
Elevify advantages
Develop skills
- Develop Markov modelling skills: construct, estimate, and validate discrete-time Markov chains efficiently.
- Master transition analysis: calculate powers of transition matrices, n-step probabilities, and mean first passage times.
- Gain expertise in stationary distributions: compute and interpret long-term equilibrium behaviours.
- Learn intervention simulation: model policy changes, compare scenarios, and evaluate outcomes with key metrics.
- Create reproducible reports: produce clear, stakeholder-focused summaries of Markov chain analyses.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workloadWhat our students say
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