Mike Gloven Will Present “Statistics & Machine Learning for Pipeline Integrity & Risk”  as a webinar on July 30, 2020 at 8 am CDT.

This training has the minimum required to hold the class. Further information to be provided upon registration

INTRODUCTION

 This webinar presents statistical and machine learning methods to support current & new regulatory requirements while at the same time optimizing integrity program costs. The webinar will demonstrate concepts & methods in the context of actual pipeline integrity data:

• Discover data most influential or important to particular threats or integrity objectives
• Identify areas of higher levels of threat susceptibility or severity
• Discover underlying data patterns to validate risk beliefs
• Find outliers which may pose extraordinary risk
• Evaluate interactive threats
• Determine optimal inspection intervals
• Measure inspection uncertainty
• Support risk mitigative decision-makingCertificate of Completion with 7.5 PDHs awarded on completion.

COURSE OUTLINE

 Session 1 (8:00 – 9:45 am)

• Machine Learning Overview & Concepts
• Application to Pipeline Integrity
• Descriptive & Inferential Statistics
  • Empirical Rule & Central Limit Theorem
  • Confidence Intervals
  • Hypothesis Testing

Session 2 (10:00 – 12:00 N)

• Machine Learning Technology Landscape
• Feature (Data) QA, Analysis & Selection
• Feature (Data) Engineering
• Outlier Analysis

Session 3 (1:00 – 2:30 pm)

• Regression Overview
• Data Preparation Concepts
• Regression Methods
• Model Performance
• Building a Regression Model & Simulations
• Prediction Scoring

Session 4 (2:45 – 4:00 pm)

• Classification Overview
• Data Preparation Concepts
• Classification Methods
• Model Performance
• Building a Classification Model & Simulations
• Prediction Scoring

Test & Review (4:15 – 5:00 pm)

• Knowledge Exam
• Review & Questions
• Submit to Instructor for Certificate

Provided:
Certificate of Completion awarding 7 PDHs
Learning materials sent electronically

By registering for this webinar, registrants and attendees agree not to make any video or audio records of the event. Neither Technical Toolboxes nor its instructors give consent to the recording of our live webinars by attendees.

Webinar Feeback
“Excellent instructor. Thee explanations were clear and the pace was good.”
“Excellent course. Very knowledgeable instructor. The examples were very useful, and starting at the basics helped lay the foundation to build what was covered later.”
“I learned a lot from this presentation, Mike was a wonderful teacher.”
“Well done, Michael.”
100% of respondents would recommend this training to a colleague within or outside of their company.

INSTRUCTOR

Mike Gloven is the managing partner of Pipeline-Risk, a provider of machine learning based integrity management and risk solutions for the oil, gas and water industries. Mike is a risk and asset management practitioner with more than 30 years of experience working as an asset and integrity manager, technical consultant, software developer, business owner and energy company executive. He is also a frequent speaker on machine learning based risk & integrity management and has led the development of numerous technology based solutions currently in use in the energy industry. He also holds on-line and on-site courses covering the practical application of machine learning to pipeline systems.

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