Antagningsdata

Välj region och språk

Välj språk för hela webbplatsen.

Publicerad utbildningskatalog

Machine Learning

Utbildningsinformation från den publicerade källan. Utbildningen och dess tidsbundna tillfällen hålls åtskilda.

Utbildningsfakta

Kod: DT150G

Machine learning is a subfield of artificial intelligence within computer science and includes techniques that enable machines (robots or software) to learn how to perform specific tasks based on data, rather than through explicit programming. Applications include image classification, predictive maintenance, text analysis, speech recognition, and the generation of images and text. This course provides an introduction to machine learning with the aim of developing an understanding of fundamental concepts, methods, and algorithms. This is achieved through hands-on work in which algorithms are implemented and modified almost from scratch, as well as through the study of data analysis, data preprocessing, model evaluation, identification of potential issues and misleading results, and practical recommendations for applying machine learning techniques. The course also includes a literature study that provides insight into current research, as well as a practical classification task and a final project that offer practical experience and skills for further studies in academia or professional work in industry with machine learning.

Behörighet

Object-Oriented Programming, 7.5 Credits from Programming, 15 credits, and Algebra and Calculus for Students in Engineering, 15 credits.

Utbildningstillfällen

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

  • Machine Learning

    Örebro University

    Örebro

    Startdatum:

    Slutdatum:

    Studietakt: 50 %

Källa och uppdatering

Skolverket Susa-navet

Hämtad: .

Publicerad: .

Visa källversion

Publiceringsversion: 8e217193-f5fa-4778-b085-a4521fd03e8d

Kontrollsumma: 1b0dc54c0fc8a359f83ba9dc8f9d468479ce432de4c03bce3b8b33dd67fe3f6c

Senast ändrad enligt källan: 2026-09-08T10:45:03