Course Outline
Foundations and Reliable Use of GenAI
- AI and GenAI fundamentals: understanding the technology, its mechanics, its value proposition, and its limitations
- Practical prompting: developing reusable prompt structures, defining clear inputs, setting constraints, and specifying output formats
- Iterative techniques: improving results through feedback loops and structured instructions
- Ensuring output quality: using checklists, cross-referencing, identifying assumptions, maintaining traceability, and setting acceptance criteria
- Standardising outputs: creating templates for technical notes, summaries, reports, and action items
- Documentation and requirements: drafting, refining, structuring, summarising, and writing change or requirement documents
- Responsible usage and data security: managing confidentiality, protecting IP, applying governance principles, and adhering to safe-use guidelines
- Hands-on exercises using realistic, anonymised scenarios
Applied Use Cases, Productivity, and Workflow Integration
- Analysis and reporting: transforming raw data 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, facilitating handovers, taking meeting minutes, and aligning stakeholders
- AI as a coding copilot: safely generating and reviewing code snippets, pseudocode, and test logic
- Accelerating knowledge work: creating reusable procedures, internal standards, and knowledge base content
- Workflow integration: establishing repeatable end-to-end processes from request to deliverable, including validation steps
- Prompt libraries and checklists: role-specific collections to enhance consistency and adoption
- Capstone exercise and 30-day adoption plan: converting a practical case study into a repeatable workflow, identifying quick wins, and establishing simple metrics
Requirements
This course is tailored for professionals in engineering, technical, and operational settings who manage documentation, structured processes, data-driven decisions, and cross-team collaboration. It is ideal for specialists and team leaders looking to boost productivity and the quality of their outputs using Generative AI in daily operations, without requiring extensive programming or data science backgrounds. The training is also beneficial for business support and operational roles that frequently engage with technical information and require more efficient, consistent, and clear 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 !
