Stochastic Processes Course
This course equips learners with essential skills in modeling and analyzing stochastic processes, including Markov chains and Poisson processes, for applications in queues, risk assessment, and environmental modeling. Participants will gain hands-on experience in simulation, parameter estimation, and communicating results effectively.

4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
This Stochastic Processes Course provides you with practical tools to construct and analyse Markov chain and Poisson process models for queues, rating transitions, and environmental extremes. You will learn to design state spaces, calibrate parameters from data, compute stationary distributions, run simulations, check numerical stability, quantify uncertainty, and present clear, defensible results to decision-makers in a concise, efficient workflow.
Elevify advantages
Develop skills
- Model Markov chains: build DTMC and CTMC models for real service and rating systems.
- Compute stationary laws: solve πP=π and πQ=0 for congestion and long-run risk.
- Apply Poisson processes: estimate λ and predict extreme-event frequencies and waits.
- Run stochastic simulations: implement DTMC/CTMC and Poisson simulation for validation.
- Communicate model results: present risks, queues, and scenarios to nontechnical teams.
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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