Antagningsdata

Välj region och språk

Välj språk för hela webbplatsen.

Publicerad utbildningskatalog

Machine Learning for Predictive Maintenance

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

Utbildningsfakta

Kod: DT8059

The courses is for professionals and part of the programme MAISTR (hh.se/maistr) where participants can study the entire programme or individual courses. The course is part of the course track machine learning and is held online in English. <br> The course covers the following topics: - Definition and terminology of relevant concepts in PdM - PdM task formulation, i.e. determine approaches and learning settings for given problems - Data engineering for time series data, including transformation, anomalous value detection, missing value imputation, outlier removal, etc. - PdM evaluation metric, given concrete applications and its formulation - Benchmarking the performance with traditional approaches - Transfer learning for fault detection and remaining useful life prediction - Survival analysis for PdM focusing on the evaluation metric and specialized cost function learning - Interpretability of the PdM machine learning models, and hybrid approaches

Behörighet

Degree of Bachelor of Science in Engineering, including an independent project 15 credits or Degree of Bachelor of Science including an independent project 15 credits or the equivalent of 180 Swedish credit points or 180 ECTS credits at an accredited university. 7.5 credits machine learning, 7.5 credits data recovery and 7.5 credits programming. English 6 or English level 2. Exemption of the requirement in Swedish is granted for those with foreign grades.

Utbildningstillfällen

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

Källa och uppdatering

Skolverket Susa-navet

Hämtad: .

Publicerad: .

Visa källversion

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

Kontrollsumma: 1b0dc54c0fc8a359f83ba9dc8f9d468479ce432de4c03bce3b8b33dd67fe3f6c

Senast ändrad enligt källan: 2026-08-28T12:40:28