Course Outline
Day 1: Foundations and Reliable Use of GenAI
AI and GenAI essentials: understanding its nature, functionality, value proposition, and limitations
Practical prompting: utilising reusable prompt structures, clear inputs, constraints, and defined output formats
Iteration techniques: refining outcomes through feedback loops and structured instructions
Output quality and verification: employing checklists, cross-checking methods, managing assumptions, ensuring traceability, and defining acceptance criteria
Standardizing deliverables: creating templates for technical notes, summaries, reports, and action items
Documentation and requirements: mastering drafting, rewriting, structuring, summarising, and requirement specification
Responsible use and data security: adhering to confidentiality protocols, IP protection, governance principles, and safe-use guidelines
Hands-on practice using realistic, anonymized scenarios
Day 2: Applied Use Cases, Productivity, and Workflow Integration
Analysis and reporting: converting raw inputs into structured insights and executive-ready summaries
Problem solving and troubleshooting: leveraging AI for root cause analysis and action planning
Cross-functional communication: enhancing decision clarity, handovers, meeting minutes, and stakeholder alignment
AI as a copilot for code and automation: safely generating and reviewing code snippets, pseudocode, and test logic
Knowledge work acceleration: developing reusable procedures, internal standards, and knowledge-base content
Workflow integration: establishing repeatable end-to-end processes from request to deliverable, incorporating validation steps
Prompt libraries and checklists: compiling role-based collections to improve consistency and adoption
Capstone practice and 30-day adoption plan: transforming one practical case per participant 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 contexts who manage documentation, structured processes, data-driven decision-making, and inter-team collaboration. It is ideal for specialists and team leads seeking to boost productivity and output quality by integrating Generative AI into daily tasks, without necessitating advanced programming or data science expertise. The course is also pertinent for operational or business support roles that frequently 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 !
