Mathematics for Artificial Intelligence II

Utbildningsfakta

Kod: MAGA85

The course consists of two modules that provide prerequisite knowledge in mathematics for technical application courses in machine learning and artificial intelligence. Module 1: Statistics and probability theory (7.5 credits) The module covers the foundations of probability and statistics theory. Key concepts include random experiments, outcomes and events, probability functions, conditional probability, random variables, standard distributions (e.g., Poisson distribution, exponential distribution, and normal distribution), measures of central tendency and dispersion, point and interval estimation, and hypothesis testing for normally distributed populations. Module 2: Optimisation (7.5 credits) The module covers linear and nonlinear optimisation, with and without constraints. Key concepts include Taylor series, necessary and sufficient conditions for optimality, convergence, Newton's method, derivative-free methods, and stochastic gradient descent methods.

Behörighet

7.5 credits from Mathematics for artificial intelligence I (15.0 credits). An equivalence assessment can be made.

Utbildningstillfällen

Varje tillfälle har egna datum och villkor. Avslutade tillfällen behålls som historik och innebär inte att en ny ansökan är öppen.

• Mathematics for Artificial Intelligence II

  Karlstad University

  Karlstad

  Startdatum: 31 augusti 2026

  Slutdatum: 17 januari 2027

  Studietakt: 50 %