Operations or supply-chain manager
Improve allocation and planning decisions.
MIT / MIT Open Learning · Universal AI
Understand AIFundamentals of Prescriptive AI and Decision-Making
Use prediction and optimisation to allocate resources under business constraints.
Curriculum
- Data-driven decision policies and policy trees.
- Linear, integer and nonlinear optimisation.
- Trade-offs, scenarios and resource allocation.
Before you start
No coding background required; code is supplied.
Who it suits
Our assessment, based on the syllabus.
Business or revenue analyst
Move from forecasts to recommended actions.
Executive sponsoring optimisation
Understand where mathematical models create value.
Expected outcomes
- Understand the difference between prediction and action.
- Practice interpreting optimisation models.
- Assess constraints and trade-offs in business decisions.
Example application
Allocate a limited fleet or staffing budget across competing demand.
Limits
- Not a course about prompting chatbots or office assistants.
- Foundational preparation, not a full operations-research qualification.
How current is it?
Part of the Universal AI curriculum launched in 2026. The course teaches established optimisation methods.
When to choose it
Consider this for staffing, allocation or planning decisions. Its optimisation focus is relevant when the task involves choosing among competing demands.
Sources
- Official course and syllabus ↗learn.mit.edu
Checked 20 October 2026. Confirm the current offer on the provider’s page before paying.