Course Outline
Foundations and Reliable Use of GenAI
- AI and GenAI fundamentals: definitions, mechanics, value propositions, and limitations
- Practical prompting: reusable prompt architectures, precise inputs, constraints, and output specifications
- Iteration methods: refining outcomes through feedback loops and structured directives
- Output quality and verification: checklists, cross-referencing, assumption management, traceability, and acceptance criteria
- Standardizing deliverables: templates for technical notes, summaries, reports, and action items
- Documentation and requirements: drafting, rewriting, structuring, summarizing, and change/requirement authoring
- Responsible use and data security: confidentiality, IP protection, governance principles, and safe-use guidelines
- Hands-on practice using realistic, anonymized scenarios
Applied Use Cases, Productivity, and Workflow Integration
- Analysis and reporting: transforming raw inputs into structured insights and executive-ready summaries
- Problem solving and troubleshooting: AI-assisted 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: secure generation and review of snippets, pseudocode, and test logic
- Knowledge work acceleration: developing reusable procedures, internal standards, and knowledge-base content
- Workflow integration: 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 metrics
Requirements
This training is tailored for professionals operating in engineering, technical, and operational settings who manage documentation, structured processes, data-informed decisions, and team collaboration. It is ideal for specialists and team leads seeking to boost productivity and output quality by utilizing Generative AI in routine tasks, without needing advanced programming or data science backgrounds. The course is also beneficial 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 !
