BEGIN:VCALENDAR VERSION:2.0 METHOD:PUBLISH PRODID:-//Tendenci - The Open Source AMS for Associations//Tendenci Codeba se MIMEDIR//EN BEGIN:VEVENT DESCRIPTION:--- This iCal file does *NOT* confirm registration.\r\nEvent d etails subject to change. ---\r\nhttps://www.spegcs.org/events/6082/\r\n\r \nEvent Title: ON DEMAND RECORDING: Machine Learning and Data Science in t he Oil and Gas Industry: Introduction, Case Studies, and Best Practices\r\ nStart Date / Time: Jan 01, 2030 08:00 AM US/Central\r\nLocation: Hyperlin k to the recording will be provided after completing your registration.\r\ nSpeaker: Patrick Bangert\r\nThis course is intended for oil and gas manag ers and professionals who want to learn about the digital transformation a nd the use of machine learning in oil and gas. The overall aim is to set y ou up for success in your data science, machine learning, artificial intel ligence projects by giving an overall understanding of the field as applie d to O&\;G.\r\nWe will begin with looking at digitization and the visio n of the digital oilfield to set the scene. The basic technological ideas of machine learning, data science, and the preparation of data will be dis cussed. The role of domain knowledge and the process of judging whether re sults are good take a central role. We discuss various practical applicati ons throughout O&\;G as well as how to assess and reap business value f rom these projects. We close by looking at project and change management a nd a brief overview of the toolsets available for this work.\r\nThis cours e is an overview and will not introduce any particular technique in detail . We will not compute anything or look at formulas or code. Rather, we wil l focus on understanding the key ideas and best practices that will make y our project a success.--- This iCal file does *NOT* confirm registration.E vent details subject to change. ---\r\n\r\n--- By Tendenci - The Open Sour ce AMS for Associations ---\r\n UID:uid6082@spegcs.org SUMMARY:ON DEMAND RECORDING: Machine Learning and Data Science in the Oil and Gas Industry: Introduction, Case Studies, and Best Practices DTSTART:20300101T140000Z DTEND:20300101T180000Z CLASS:PUBLIC PRIORITY:5 DTSTAMP:20240329T091513Z TRANSP:OPAQUE SEQUENCE:0 LOCATION:Hyperlink to the recording will be provided after completing your registration. X-ALT-DESC;FMTTYPE=text/html:
This course is intended for oil and gas managers and professionals who want to learn abou t the digital transformation and the use of machine learning in oil and ga s. The overall aim is to set you up for success in your data science, mach ine learning, artificial intelligence projects by giving an overall unders tanding of the field as applied to O&\;G.
We will begin with loo king at digitization and the vision of the digital oilfield to set the sce ne. The basic technological ideas of machine learning, data science, and t he preparation of data will be discussed. The role of domain knowledge and the process of judging whether results are good take a central role. We d iscuss various practical applications throughout O&\;G as well as how t o assess and reap business value from these projects. We close by looking at project and change management and a brief overview of the toolsets avai lable for this work.
This course is an overview and will not introd uce any particular technique in detail. We will not compute anything or lo ok at formulas or code. Rather, we will focus on understanding the key ide as and best practices that will make your project a success.