Markov Chain Course
Master Markov chains using real engagement data. Gain skills to construct transition matrices, analyse short- and long-term behaviour, model interventions, and convert stochastic insights into clear, actionable recommendations for impactful mathematical decisions. This course provides hands-on experience with data cleaning, exploration, matrix estimation, dynamics analysis, stationary distributions, assumption testing, scenario comparison, and reproducible reporting with quantified uncertainty.

4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
This Markov Chain Course offers a focused, practical approach to modelling weekly engagement logs. Participants will clean and explore data, estimate transition matrices, analyse short- and long-term dynamics, compute stationary distributions, test assumptions, model interventions, compare scenarios, and produce clear, reproducible reports featuring actionable recommendations and quantified uncertainty.
Elevify advantages
Develop skills
- Markov modelling: build, estimate, and validate discrete-time Markov chains quickly.
- Transition analysis: compute P, P², n-step transitions, and mean first passage times.
- Stationary insights: derive stationary distributions and interpret long-run behaviour.
- Intervention design: simulate policy changes and compare scenarios with clear metrics.
- Reproducible reporting: create concise, stakeholder-ready Markov chain reports.
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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