The Pipeline Pigging and Integrity Management Conference (PPIM) is offering a new course in 2020: Practical Application of Machine Learning to Pipeline Integrity.
The course is a hands-on practical and interactive learning course that will take place from 8am to 5pm on 17 and 18 February of PPIM.
Attendees will learn how to apply inferential statistical and machine learning methods to common pipeline integrity and risk management use cases while using data with open source software to experience its practical application.
The objective is for each attendee to learn how machine learning methods can support many cases, including:
- learn and validate data driven algorithms
- validate existing rule-based algorithms
- measure the influence and importance of underlying threat data
- infer missing or unknown data
- establish optimal assessment intervals
- support the assessment of un-piggable pipelines
- support monetised risk-based decision making.
The course is targeted at integrity managers and engineers, risk managers and engineers, and data analysts who, upon course completion, will be awarded 1.4 CEUs.
The course will be run by Expert Infra Solutions (EIS) Managing Director Michael Gloven.
For more information visit the PPIM website.
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