This course offers a practical introduction to how mathematical optimisation can support better decision-making in complex, real-world situations. It is open to anyone interested in understanding how to model and solve problems involving limited resources and competing objectives, regardless of background. Core topics include linear, integer, and nonlinear optimisation, with a focus on real applications in areas such as transport, health, and energy. The course highlights how mathematical modelling can help balance trade-offs, improve efficiency, and support sustainable and data-driven decisions.

Syllabus

Learning Outcomes

After completing the course, the student:

Recognises the role of optimisation in addressing societal challenges such as transport, health, and energy.
Understands the fundamental elements of an optimisation model and how they support decision-making.
Formulates real-world problems in a way that makes them suitable for mathematical optimisation modelling.
Evaluates how optimisation informs practical choices, while acknowledging its assumptions and limitations.

Content and Schedule

The course consists of video lectures and quizzes. You can complete the content flexibly at your own pace.

Modules:

Functions and optimisation
Mathematical programming
Mathematical programming models: examples
Symbolic formulation
Mathematical programming models: more examples
Modelling integer decisions
Mathematical programming models: (mixed-)integer examples
Multi-objective optimisation
Nonlinear optimisation

The course takes approximately 27 hours to complete and is equivalent to 1 ECTS. It consists of video lectures, along with quizzes, and modelling exercises that support learning.

You can complete the course at your own pace, either by spreading the content over several weeks or by following a more focused schedule. To finish the course and receive a certificate, you need to watch all videos and complete the quizzes with a minimum score of 75 percent.

For Whom?

This course is designed for individuals who want to understand how mathematical optimisation can be applied in practice. It is particularly suitable for:

Higher education students looking to build foundational knowledge in optimisation
Early-career professionals seeking to apply mathematical modelling in their work
Advanced professionals and academics aiming to deepen their skills in optimisation and mathematical programming for real-world decision-making