Decision Science Course
Decision Science gives you a rigorous, end-to-end framework for making smarter choices under uncertainty. From probability theory and Bayesian analysis to game theory and optimisation, this course covers the full analytical toolkit. You will learn to structure complex problems, evaluate trade-offs, and deliver defensible recommendations that drive real results.
flexible workload of 4 to 360h
valid certificate in your country
What will I learn?
You will master the core methods of decision science, starting with probability fundamentals and Bayesian updating and moving through decision trees, utility theory, and multi-criteria analysis. You will learn how to build and solve optimisation models, apply game theory to competitive situations, and use Monte Carlo simulation to quantify risk. The course also covers behavioural biases, forecasting techniques, and data visualisation for communicating results to stakeholders. By the end, you will be equipped to design and implement analytical decision processes in any organisational setting.
Elevify advantages
Develop skills
- Probability Modelling: Quantify uncertainty and apply Bayesian reasoning to real decision problems.
- Decision Tree Analysis: Build and solve multi-stage decision models using rollback methods.
- Multi-Criteria Evaluation: Score and rank competing alternatives across conflicting organisational objectives.
- Optimisation Formulation: Construct linear and stochastic programmes to prescribe data-driven decisions.
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 workloadWhat our students say
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