Markov Chain Course
Gain expertise in Markov chains using real-world engagement data. Master building transition matrices, analysing transient and steady-state behaviours, simulating policy interventions, and transforming probabilistic insights into actionable, high-impact recommendations for informed 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. Learners will clean data, build transition matrices, study short-term and long-term patterns, calculate stationary distributions, test key assumptions, simulate interventions, compare different scenarios, and produce clear reports with recommendations backed by quantified uncertainty measures.
Elevify advantages
Develop skills
- Markov chain modelling: rapidly construct, estimate, and validate discrete-time Markov chains.
- Transition matrix analysis: calculate powers, multi-step probabilities, and mean first passage times.
- Stationary distribution analysis: compute and interpret long-term equilibrium behaviours.
- Intervention simulation: model policy changes and evaluate scenarios using precise metrics.
- Reproducible reporting: develop clear, stakeholder-focused reports on Markov chain findings.
Suggested summary
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