Course Outline
Foundations and Reliable Use of GenAI
- Essentials of AI and GenAI: understanding its nature, mechanics, value-add, and limitations
- Practical prompting: implementing reusable prompt structures, clear inputs, constraints, and specified output formats
- Iteration techniques: enhancing results through feedback loops and structured instructions
- Output quality and verification: utilising checklists, cross-checking, assumptions, traceability, and acceptance criteria
- Standardising deliverables: creating templates for technical notes, summaries, reports, and action items
- Documentation and requirements: drafting, rewriting, structuring, summarising, and writing changes and requirements
- Responsible use and data security: ensuring confidentiality, IP protection, governance principles, and safe usage rules
- Practical exercises using realistic, anonymised scenarios
Applied Use Cases, Productivity, and Workflow Integration
- Analysis and reporting: transforming raw inputs into structured insights and executive-level summaries
- Problem solving and troubleshooting: AI-assisted root cause analysis and action planning
- Cross-functional communication: clarifying decisions, managing handovers, documenting meeting minutes, and aligning stakeholders
- AI as a copilot for code and automation: safely generating and reviewing 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: converting one practical case per participant into a repeatable workflow, focusing on quick wins and simple measurement
Requirements
This training is tailored for professionals in engineering, technical, and operational settings who manage documentation, structured processes, data-driven decision-making, and team collaboration. It is ideal for specialists and team leaders seeking to enhance productivity and output quality through the use of Generative AI in routine tasks, without requiring advanced programming or data science expertise. The course is also pertinent to 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 !
