Markov Chain Course
Gain expertise in Markov chains using real engagement data. Build and analyse transition matrices, examine short- and long-term dynamics, simulate interventions, and deliver actionable stochastic insights for informed mathematical decision-making in dynamic systems.

from 4 to 360h flexible workload
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, transition matrix estimation, analysis of short- and long-term patterns, stationary distribution calculations, assumption testing, intervention modelling, scenario comparisons, and production of reproducible reports with recommendations and uncertainty measures.
Elevify advantages
Develop skills
- Markov chain modelling: construct, estimate, and validate discrete-time chains efficiently.
- Transition matrix analysis: calculate powers, n-step transitions, and first passage times.
- Stationary distribution analysis: compute and interpret long-term equilibrium behaviours.
- Intervention simulation: model policy impacts and evaluate scenarios using key metrics.
- Reproducible reporting: produce clear, stakeholder-focused 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 workload.What our students say
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