Course Outline
Day 1: Foundations and Reliable Use of GenAI
Core concepts of AI and Generative AI: understanding its functionality, value-addition points, and limitations
Prompt engineering basics: utilizing reusable prompt structures, defining clear inputs, constraints, and output formats
Refinement techniques: improving results through iterative feedback loops and structured instructions
Ensuring output quality and verification: employing checklists, cross-referencing, identifying assumptions, ensuring traceability, and meeting acceptance criteria
Standardizing outputs: creating templates for technical notes, summaries, reports, and action items
Documentation and requirements management: techniques for drafting, rewriting, structuring, summarizing, and authoring change/requirement documents
Responsible AI usage and data security: guidelines for confidentiality, IP protection, governance principles, and safe-use protocols
Practical exercises using realistic, anonymized scenarios
Day 2: Applied Use Cases, Productivity, and Workflow Integration
Analysis and reporting: transforming raw inputs into structured insights and executive-ready summaries
Problem solving and troubleshooting: leveraging AI for root cause analysis and action planning
Enhancing cross-functional communication: improving decision clarity, handovers, meeting minutes, and stakeholder alignment
AI as a coding copilot: safely generating and reviewing code 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-specific collections designed to enhance consistency and adoption
Capstone project and 30-day adoption plan: transforming one practical case per participant into a repeatable workflow, identifying quick wins and establishing simple measurement metrics
Requirements
This training is tailored for professionals in engineering, technical, and operational fields who manage documentation, structured processes, data-driven decision-making, and cross-team collaboration. It is ideal for specialists and team leaders seeking to boost productivity and output quality using Generative AI in their daily tasks, without necessitating advanced programming or data science expertise. The curriculum 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 !
