Course Outline
Day 1: Foundations and Reliable Use of GenAI
Core concepts of AI and GenAI: understanding functionality, value proposition, and limitations
Effective prompting: utilising reusable prompt structures, defining clear inputs, constraints, and output formats
Iteration techniques: refining results via feedback loops and structured instructions
Ensuring output quality and verification: employing checklists, cross-checking methods, managing assumptions, ensuring traceability, and defining acceptance criteria
Standardising deliverables: creating templates for technical notes, summaries, reports, and action items
Managing documentation and requirements: skills in drafting, rewriting, structuring, summarising, and writing change/requirement specifications
Responsible use and data security: upholding confidentiality, protecting intellectual property, understanding governance principles, and adhering to safe-use protocols
Practical exercises using realistic, anonymised scenarios
Day 2: Applied Use Cases, Productivity, and Workflow Integration
Analysis and reporting: transforming raw inputs into structured insights and executive-ready summaries
Problem solving and troubleshooting: leveraging AI for root cause analysis and action planning
Enhancing cross-functional communication: achieving decision clarity, managing handovers, drafting meeting minutes, and aligning stakeholders
AI as a coding and automation copilot: safely generating and reviewing code snippets, pseudocode, and test logic
Accelerating knowledge work: developing reusable procedures, internal standards, and knowledge-base content
Integrating into workflows: establishing repeatable end-to-end processes from request to deliverable, including validation steps
Building prompt libraries and checklists: curating role-based collections to improve consistency and adoption
Capstone exercise and 30-day adoption plan: each participant will transform one practical case into a repeatable workflow, identifying quick wins and establishing simple measurement metrics
Requirements
This training is tailored for professionals operating in engineering, technical, and environmental settings who manage documentation, structured processes, data-driven decision-making, and inter-team collaboration. It is ideal for specialists and team leads seeking to enhance productivity and output quality through the integration of Generative AI in everyday tasks, without the need for advanced programming or data science expertise. The course is also highly relevant for operational or business support roles that regularly engage with technical information and require clearer, faster, and more consistent deliverables.
Testimonials (3)
The extensive selection of tools presented
Miruna Buzduga - Aeronamic Eastern Europe
Course - AI Enablement Training for Engineers
The training style, preparation quality and focus on the important/relevant points, good tips, opening for any question with complete answers, info share willing, overall the high know how of the trainer combined with the training method.
Teofil Laurentiu Sasu - Aeronamic Eastern Europe
Course - AI Enablement Training for Engineers
Almost everything !
