The digital learning ecosystem An efficient management approach to capability development, delivering smarter teams, improved productivity and better business outcome for the managers.
Bridging industry with academia An immersive and collaborative learning experience event, using OilSim simulator, providing highly relevant industry knowledge and soft skills.
The digital learning ecosystem Digitally and seamlessly connecting you, the learner, with pertinent learning objects and related technologies ensuring systematic, engaging and continued learning.
Industry and client recognition
Best Outreach Program Finalist: WorldOil Awards
Overall Customer Satisfaction Score
Training provider of the year: 2013, 14 and 15
Upstream learning simulator With more than 50,000 participants instructed in various disciplines, data driven OilSim runs real-world oil and gas business scenarios and technical challenges.
Engaging. Educational. EnjoyableUpstream learning simulator With more than 50,000 participants instructed in various disciplines, data driven OilSim runs real-world oil and gas business scenarios and technical challenges.
Engaging. Educational. EnjoyableBridging industry with academia An immersive and collaborative learning experience event, using OilSim simulator, providing highly relevant industry knowledge and soft skills.
The digital learning ecosystem Digitally and seamlessly connecting you, the learner, with pertinent learning objects and related technologies ensuring systematic, engaging and continued learning.
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Develop measurable skills and capabilities
This three-day, hands-on course is designed for energy professionals in subsurface and production seeking to apply Generative AI (GenAI) solutions to industry challenges.
Participants will gain practical skills in LLMs, prompt engineering, Retrieval-Augmented Generation (RAG), fine-tuning, multi-agent systems, and No-Code platforms.
Through lectures, live demos, and hands-on projects, attendees will learn to build and deploy AI-powered applications tailored to energy sector workflows.
Introduction to GenAI & Prompt Engineering
• Lecture: Introduction to Generative AI and its applications in the energy sector.
• Live Demo and Coding: Setting up Large Language Models (LLMs) in Python and performing text analysis.
• Lecture: Fundamentals of prompt engineering, covering best practices and advanced techniques.
• Live Demo and Coding: Live coding session on basic and advanced prompt engineering tailored for oil and gas data.
Retrieval-Augmented Generation (RAG) and Fine-Tuning
• Lecture: Introduction to RAG and fine-tuning, their significance, and applications in the energy industry.
• Live Demo and Coding: RAG Implementation walkthrough with code snippets integrating data for a dynamic chat experience.
• Live Demo and Coding: Fine-tuning a model for energy-specific applications.
• Hands-On Project: Implement a RAG-powered system to interact with geological well report data
Multi-Agent Systems & No-Code AI Platforms
• Lecture: Introduction to multi-agent systems and their role in GenAI applications for the energy sector.
• Live Demo and Coding: Building an agentic system using LLMs to conduct research on energy-related topics and generate a structured report.
• Lecture: Overview of No-Code AI platforms and how they can be used for rapid prototyping and deployment of GenAI applications.
• Live Demo: Walkthrough of a GenAI-powered workflow using a No-Code platform.
• Hands-On Project: Implement a multi-agent workflow where agents work collaboratively to plan, estimate costs, and optimize resource allocation for a field development project.
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