Course Outline
Foundations and Reliable Use of GenAI
- AI and GenAI essentials: what it is, how it works, where it adds value, and where it fails
- Practical prompting: reusable prompt structures, clear inputs, constraints, and output formats
- Iteration techniques: refining results through feedback loops and structured instructions
- Output quality and verification: checklists, cross-checking, assumptions, traceability, acceptance criteria
- Standardizing deliverables: templates for technical notes, summaries, reports, and action items
- Documentation and requirements: drafting, rewriting, structuring, summarizing, and change/requirement writing
- Responsible use and data security: confidentiality, IP protection, governance principles, and safe-use rules
- Hands-on practice with realistic, anonymized scenarios
Applied Use Cases, Productivity, and Workflow Integration
- Analysis and reporting: converting raw inputs into structured insights and executive-ready summaries
- Problem solving and troubleshooting: AI-supported root cause analysis and action planning
- Cross-functional communication: 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
- Knowledge work acceleration: building reusable procedures, internal standards, and knowledge-base content
- Workflow integration: repeatable end-to-end processes from request to deliverable, with validation steps
- Prompt libraries and checklists: role-based collections to improve consistency and adoption
- Capstone practice and 30-day adoption plan: one practical case per participant turned into a repeatable workflow, with quick wins and simple measurement
Requirements
This training is designed for professionals working in engineering, technical, and operational environments who handle documentation, structured processes, data-driven decisions, and collaboration across teams. It is suitable for specialists and team leads who want to improve productivity and output quality using Generative AI in everyday tasks, without requiring advanced programming or data science experience. The course is also relevant for operational or business support roles that frequently interact with technical information and need 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 !
