"Our tailored course provided a well rounded introduction and also covered some intermediate level topics that we needed to know. Clive gave us some best practice ideas and tips to take away. Fast paced but the instructor never lost any of the delegates"
Brian Leek, Data Analyst, May 2022
By the end of the day, participants will be able to:
Session 1: AI, Real Assets & Executive Accountability
Purpose - Frame AI as a leadership and governance issue, not a technology project.
Key Topics
Outputs
Individual executive action plan Key questions to take back to:Session 6: Executive Action Planning & Board Readiness
Purpose - Ensure leaders leave board-ready.
Key Topics
What boards will ask about AI in real assets Framing AI decisions in:Group Exercise
90-Day / 12-Month / 3-Year AI Roadmap
Session 5: AI Roadmapping for Asset-Intensive Organisations
Purpose - Translate insight into a realistic, staged roadmap.
Key Topics
Sequencing AI initiatives:Discussion
What decisions should never be fully automated in asset environments?
Session 4: Governance, Risk & Responsible AI Oversight
Purpose - Equip leaders to govern AI safely and credibly.
Key Topics
Executive-level AI governance models Oversight vs management vs implementation Key risks:
Executive Exercise
Data Trust Stress Test:
Session 3: Data Integrity, Quality & Trust in AI Systems
Purpose - Address the real blocker: data trust.
Key Topics
Why AI amplifies data integrity problems Common data failures in asset-heavy environments:Case Examples
Utilities, transport, property portfolios, energy assets Where AI delivered value — and where it didn’t
Session 2: Asset Performance & Value Creation with AI
Purpose - Focus on commercially defensible use cases tied to asset value.
Key Topics
AI applications across the asset lifecycle:Discussion
“Where are we currently exposed — through not using AI?”
VPs, Directors, Heads of Asset Management, Data Integrity, Engineering, Digital, Risk, Compliance, and Transformation in asset-intensive organisations.
"Our tailored course provided a well rounded introduction and also covered some intermediate level topics that we needed to know. Clive gave us some best practice ideas and tips to take away. Fast paced but the instructor never lost any of the delegates"
Brian Leek, Data Analyst, May 2022
Sign up for the JBI Training newsletter to receive technology tips directly from our instructors - Analytics, AI, ML, DevOps, Web, Backend and Security.
This senior-level course shows how AI can enhance asset performance and decision-making without compromising safety, data integrity, or governance.
It helps leaders identify high-value AI opportunities while avoiding low-ROI initiatives.
Participants gain clarity on using AI to improve reliability, lifecycle management, and operational outcomes. The programme strengthens executive capability in assessing risk, governance, and accountability in AI solutions. By the end, leaders can define a credible, responsible AI roadmap aligned to asset strategy and regulation.
1. What is the target audience for this course?
This course is designed for data analysts, data scientists, machine learning engineers, and anyone interested in leveraging Language Models (LLMs) for data analysis tasks. Whether you're a beginner or an experienced professional looking to enhance your skills, this course offers valuable insights into mastering LLMs for advanced data analysis.
2. Are there any prerequisites for enrolling in this course?
While there are no strict prerequisites, a basic understanding of machine learning concepts and familiarity with Python programming language will be beneficial. Participants with a background in data analysis or related fields will find the course content more accessible, but individuals with a keen interest in data analysis are also welcome to enroll.
3. What can I expect to learn from this course?
Throughout the course, you will gain a comprehensive understanding of Language Models and their applications in data analysis. You will learn how to train and fine-tune LLMs using popular frameworks such as TensorFlow or PyTorch. Additionally, you will explore ethical considerations and potential biases in LLM-based data analysis, ensuring responsible and reliable data interpretation.
4. Will there be practical exercises and hands-on training sessions?
Yes, the course includes practical exercises and hands-on training sessions aimed at reinforcing your understanding of LLMs and data analysis techniques. You will have the opportunity to apply theoretical concepts in real-world scenarios, allowing for a deeper immersion into the subject matter.
5. How will this course benefit my career in data analysis?
By mastering LLMs and advanced data analysis techniques, you will significantly enhance your skill set and marketability in the field of data analysis. The knowledge and expertise gained from this course will open up new opportunities for career advancement and enable you to tackle complex data analysis challenges with confidence and proficiency.
CONTACT
+44 (0)20 8446 7555
Copyright © 2025 JBI Training. All Rights Reserved.
JB International Training Ltd - Company Registration Number: 08458005
Registered Address: Wohl Enterprise Hub, 2B Redbourne Avenue, London, N3 2BS
Modern Slavery Statement & Corporate Policies | Terms & Conditions | Contact Us
POPULAR
AI training courses CoPilot training course
Threat modelling training course Python for data analysts training course
Power BI training course Machine Learning training course
Spring Boot Microservices training course Terraform training course
