Course Outline
Day 1: Foundations and Reliable Use of GenAI
AI and GenAI essentials: definition, functionality, value addition, and limitations
Practical prompting: reusable prompt structures, precise inputs, constraints, and output formats
Iteration techniques: refining outcomes through feedback loops and structured instructions
Output quality and verification: checklists, cross-checking, assumptions, traceability, and acceptance criteria
Standardizing deliverables: templates for technical notes, summaries, reports, and action items
Documentation and requirements: drafting, rewriting, structuring, summarising, and requirement writing
Responsible use and data security: confidentiality, IP protection, governance principles, and safe-use protocols
Hands-on practice with realistic, anonymized scenarios
Day 2: 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 tailored for professionals operating in engineering, technical, and environmental settings who manage documentation, structured processes, data-driven decision-making, and inter-team collaboration. It is ideal for specialists and team leaders seeking to enhance productivity and output quality by integrating Generative AI into daily tasks, without necessitating advanced programming or data science expertise. The course is also pertinent 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 !
