Course content

Probability theory

Discrete Probability. Expectation and variance. Simulations.

Logic

Bitwise logic. Negative and floating point numbers in binary.

Linear Algebra

Matrix algebra, programming with matrices, linear systems of equations, least squares method

Geometry.

Trigonometry and vectors2. Transformations in 2 and 3 dimensions. Rotations, Euler angles and quaternions

Procedural Methods

Perlin noise and midpoint displacement. Interpolation.

Mechanics

Differentiation and integration. Newtons laws. Elastic collisions. Particle systems.

Introduction to functional programming in Python.

Learning outcome

Knowledge about:

• Applications of mathematics in programming
• Elementary mechanics for games/applications
• The role of mathematics in software development

Skills in:

• Translating mathematics to code
• Using relevant mathematical symbols and formulas
• Applying mathematical libraries
• General logical and mathematical reasoning

General competencies:

• Problem solving and description of problems and their solutions
• Programming
• Written communication in English

Learning methods and activities

• Lectures and tutorials
• Compulsory assignments

Compulsory assignments

• Assignments

Recommended previous knowledge

Mathematics from secondary education and one mathematics course for computer science. One programming course, e.g. using C++.

Course materials

Published notes and downloadable books. Web resources.