Markov Chain Course
Dive into Markov chains using real-world engagement data in this comprehensive course. Build and estimate transition matrices, analyze transient and steady-state behaviors, design interventions, compare outcomes, and deliver actionable, uncertainty-aware recommendations to drive informed mathematical strategies. Gain hands-on skills for modeling stochastic processes effectively.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This course provides a practical guide to using Markov chains for analyzing weekly engagement data. Participants will clean and explore datasets, build transition matrices, examine short-term and long-term patterns, calculate stationary distributions, validate models, simulate interventions, evaluate scenarios, and produce reproducible reports with quantified uncertainties and practical advice.
Elevify advantages
Develop skills
- Markov modeling: rapidly construct, estimate, and validate discrete-time Markov chains.
- Transition analysis: calculate powers of matrices, n-step transitions, and mean first passage times.
- Stationary insights: compute and interpret stationary distributions for long-term predictions.
- Intervention design: model policy impacts, simulate changes, and compare results using key metrics.
- Reproducible reporting: produce clear, concise reports tailored for stakeholders.
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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