Markov Chain Course
Master Markov chains using real engagement data. Build transition matrices, analyse short- and long-term behaviour, model interventions, and transform stochastic insights into clear, actionable recommendations for high-impact mathematical decisions. This course provides hands-on experience with data cleaning, exploration, assumption testing, scenario comparison, and reproducible reporting with quantified uncertainty.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This Markov Chain Course offers a focused, hands-on approach to modelling weekly engagement logs. 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 with actionable recommendations and quantified uncertainty.
Elevify advantages
Develop skills
- Markov modeling: build, estimate, and validate discrete-time Markov chains fast.
- Transition analysis: compute P, P², n-step moves, 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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