Markov Chain Course
Gain expertise in Markov chains using real-world engagement data. Build and analyse transition matrices, explore short- and long-term dynamics, simulate interventions, and deliver actionable insights with quantified uncertainty to support strategic decisions in data-driven environments.
flexible workload from 4 to 360h
valid certificate in your country
What will I learn?
This course provides a practical guide to using Markov chains for analysing weekly user engagement data. Participants will learn data cleaning and exploration techniques, transition matrix estimation, analysis of short-term and long-term patterns, and calculation of stationary distributions. Key skills include testing model assumptions, simulating interventions, comparing different scenarios, and producing clear reports with recommendations backed by quantified uncertainty measures.
Elevify advantages
Develop skills
- Markov chain modelling: quickly construct, estimate, and validate discrete-time Markov chains.
- Transition matrix analysis: calculate powers, n-step transitions, and mean first passage times.
- Stationary distribution analysis: compute and interpret long-term equilibrium behaviours.
- Intervention simulation: model policy changes and evaluate scenarios using key performance metrics.
- Reproducible reporting: produce stakeholder-friendly reports on Markov chain findings.
Suggested summary
Before starting, you can change the chapters and 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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