Foundations of AI and Optimisation Methods
Karlstad University
Karlstad
Startdatum:
Slutdatum:
Studietakt: 50 %
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Kod: DVAE23
The course comprises two parts. The first part, which constitutes approximately 60% of the course, treats basic concepts and paradigms of artificial intelligence and machine learning, for instance hypothesis space, generalisation error, and limitations. This first part of the course also includes practical components, such as design of algorithms for linear and logistic regression and support vector machines, and practical aspects of machine learning, for instance normalisation and cross-validation. The second part of the course treats optimisation with and without constraints. Among other things, this includes showing how stochastic gradient descent can be used for optimisation without constraints.
Calculus and geometry (7.5 ECTS credits), Calculus in several variables (7.5 ECTS credits), Data structures and algorithms (7.5 ECTS credits), and upper secondary level English 6, or equivalent
Varje tillfälle har egna datum och villkor. Avslutade tillfällen behålls som historik och innebär inte att en ny ansökan är öppen.
Karlstad University
Karlstad
Startdatum:
Slutdatum:
Studietakt: 50 %
Hämtad: .
Publicerad: .
Publiceringsversion: 8e217193-f5fa-4778-b085-a4521fd03e8d
Kontrollsumma: 1b0dc54c0fc8a359f83ba9dc8f9d468479ce432de4c03bce3b8b33dd67fe3f6c
Senast ändrad enligt källan: 2026-03-03T14:09:59