Machine Learning for Predictive Maintenance
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.
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
Level:
Advanced level
Application code:
23557
Entry requirements:
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 learing, 7.5 credits data recovery and 7.5 credits programming. Applicants must have written and verbal command of the English language equivalent to English course 6 in Swedish Upper-Secondary School. Exemption of the requirement in Swedish is granted.
Selection rules:
Credits: 100%
Start week:
week: 14
Number of gatherings:
0
Instructional time:
Various times
Tuition fee:
Language of instruction:
Teaching is in English.
