Mathematical Modeling Courses

​​What is mathematical modeling?

Mathematical modeling describes systems using math methodologies. Quite a few fields use mathematical modeling to describe concepts and visualize predictions--engineering, the natural sciences, and social science, to name a few.

Using math to visualize real-world data provides researchers and developers with better observation and validation tools. It can help with optimization in the business world and offer support working with nonlinear data.

Mathematical models take different forms:

• statistical models

• differential equations

• logical models

• dynamical systems

• game theory models

They're composed of correlations--relationships and variables. Mathematicians classify models by this structure:

• linear versus nonlinear

• dynamic versus static

• explicit versus implicit

• discrete versus continuous

• strategic versus non-strategic

• deterministic versus probalistic

• deductive versus inductive versus floating

Models help explain systems and to study how components work, especially if changes are infrequent or seemingly random. They can also help lay the foundation for better predictions based on past activity and observations.

Learning about mathematical models

​edX offers courses designed in partnership with leading thinkers in the field of mathematics and analytics. Students explore courses for free for personal growth and collaborate with like-minded peers from around the world.

edX also offers official tracks. Once students pay the fee, they receive lifetime access to the course and its materials, along with official grades and progress reports. Participants get an official certificate of completion once they satisfy all course requirements. The platform offers single courses, certificates, and micro or full degrees.

Mathematical modeling courses and certificates

Students can participate in a variety of mathematics courses on the modeling of real-world problems. High Dimensional Data Analysis from HarvardX offers training in several mathematical techniques for this type of data, including clustering, heat maps, and dimension reduction. 

Purdue University offers Probability: Basic Concepts & Discrete Random Variables. The course covers widely used probability models, discrete random variables, and joint distributions and expected values. Students explore these formulations to help master data science modeling techniques or to brush up on the complex math for other purposes. 

Data Analysis for Life Sciences is a professional certificate series covering differential equations, linear algebra, and other modeling activities specifically used for data in fields like biomedical or epidemiology. Students will master the algorithms that help with forecasting, building dynamic models, and examining components.

Learn mathematical modeling with edX

edX offers training in the types of models that shed light on big data. Students participating in mathematical modeling courses can work in fields like public health, research new drug delivery in biotech, or just study the world around them on their own time. Mathematical modeling forms the foundation of neural networks and can examine datasets to determine the best course of action for infectious disease epidemics. In short, students can learn to examine everything with edX along the way.