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En lärare förklarar för två studenter. Foto.
The technical content of the course, covered through lectures, exercises and laboratory work, reviews concepts and topics, which students are expected to have some familiarity with from previous studies. These include models for stochastic dependence, describing dynamical multivariable systems using time-invariant ordinary differential equations, transfer functions and state space representations, stability assessment, robustness margins, synthesis, and implementation of controllers.

FACTS


CYCLE

Second cycle

ENTRY REQUIREMENTS

General entry requirements and approved result from the following course/courses:
IAI600-Introduction to Artificial Intelligence and Machine Learning or the equivalent.

PACE OF STUDY

Part-time

TYPE OF INSTRUCTION

On Campus

PROGRAMME/COURSE DATE


SPRING 2024

SPRING 2024

SPRING 2025

SPRING 2025

TEACHING HOURS

Daytime

APPLICATION DEADLINE

16 October 2023

APPLICATION CODE

HV-E1777

START/END

From v.13 2024 to v.22 2024

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