MACHINE LEARNING FOR PIPELINE INTEGRITY & RISK
Led by Mike Gloven and Justin Raimondi
November 2-3, 2021 | Online
What you will learn
Led by Mike Gloven and Justin Raimondi, this course will present the basics of machine learning and how the process is used to support integrity and risk management. You will learn:
- Data sampling, preparation & quality assurance methods
- Feature analysis & engineering
- Classification & cluster learning methods
- Regression learning methods
- Basics of inferential statistics & sampling
- Outlier detection
- Model validation
- Machine learning based risk
- Where to go to learn & perform your own machine learning
Course structure and delivery
The course consists of:
- Pre-recorded topical lectures comprising a total of 8 hours over two days (4 hours a day).
- The delivery platform will be GoToWebinar.
- The instructors will be online with you during the Lecture sessions.
- Live Question & Answer and live demonstration sessions with the instructors that will follow each lecture. 20 minutes per session.
- You will be able to submit your questions to the instructors via live Chat during the lecture sessions, and they will address them in the Q&A session that follows.
- Access to a recording of the course afterward.
- Attendees will have free use of the basic Pipeline-Risk learning platform for 30 days.
Who should attend
This is an introductory course designed for asset, integrity & risk engineers & managers. A background in math or statistics is useful as well as an understanding of common integrity use cases.
The complete course presentation material will be available through the private course website. Logins will be distributed after registration.
Recording available after the course
You can access the entire webinar-course recording online for 14 days following the webinar sessions.
Continuing Education Units
Upon completion of the course, participants will be eligible to receive .7 Continuing Education Units.