Course Outline
Foundations and Reliable Use of GenAI
- Essentials of AI and GenAI: understanding definitions, mechanics, value-adds, and limitations
- Practical prompting: reusable prompt structures, precise inputs, constraints, and output formatting
- Iteration techniques: refining outcomes through feedback loops and structured directives
- Output quality and verification: checklists, cross-verification, assumption tracking, traceability, and acceptance criteria
- Standardising deliverables: templates for technical notes, summaries, reports, and action items
- Documentation and requirements: drafting, rewriting, structuring, summarising, and change/requirement authoring
- Responsible usage and data security: confidentiality, IP protection, governance principles, and safe-use protocols
- Hands-on practice using realistic, anonymised scenarios
Applied Use Cases, Productivity, and Workflow Integration
- Analysis and reporting: converting raw data into structured insights and executive-ready summaries
- Problem solving and troubleshooting: AI-assisted 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: safe generation and review of snippets, pseudocode, and test logic
- Accelerating knowledge work: developing 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-based collections to enhance consistency and adoption
- Capstone practice and 30-day adoption plan: translating one practical case per participant into a repeatable workflow, focusing on quick wins and simple metrics
Requirements
Designed for professionals operating in engineering, technical, and operational settings, this training suits those involved in documentation, structured processes, data-driven decision-making, and inter-team collaboration. It is ideal for specialists and team leaders seeking to boost productivity and output quality by integrating Generative AI into daily tasks, without necessitating advanced programming or data science expertise. The course also benefits 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 !
