Markov Chain Course
Master Markov chains using real engagement data. Build transition matrices, analyse transient and steady-state behaviours, model policy interventions, and transform probabilistic analyses into precise, actionable recommendations for optimal decision-making in dynamic systems.

4 to 360 hours of flexible workload
certificate valid in your country
What Will I Learn?
Gain hands-on skills in Markov chain modelling for weekly engagement data. Clean and explore datasets, estimate transition matrices, analyse short- and long-term dynamics, compute stationary distributions, test assumptions, simulate interventions, compare scenarios, and produce reproducible reports with actionable insights and uncertainty quantification.
Elevify Advantages
Develop Skills
- Markov modelling: rapidly construct, estimate, and validate discrete-time Markov chains.
- Transition analysis: calculate powers of transition matrices, n-step probabilities, and mean first passage times.
- Stationary analysis: compute and interpret stationary distributions for long-term predictions.
- Intervention simulation: model policy impacts, compare alternatives using key performance metrics.
- Reproducible reporting: develop clear, stakeholder-focused reports on Markov chain findings.
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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