Markov Chain Course
Master Markov chains using real engagement data in this hands-on course. Build transition matrices, analyze short- and long-term dynamics, model interventions, compute stationary distributions, and deliver actionable recommendations with quantified uncertainty for impactful decisions.

4 to 360h flexible workload
certificate valid in your country
What will I learn?
This course provides a focused, hands-on approach to modeling weekly engagement logs with Markov chains. Clean and explore data, estimate transition matrices, analyze short- and long-term dynamics, compute stationary distributions, test assumptions, model interventions, compare scenarios, and produce reproducible reports with actionable insights and uncertainty quantification.
Elevify advantages
Develop skills
- Markov modeling: 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 behavior.
- 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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