Course Outline
Day 1: Foundational Principles and Responsible Deployment of Generative AI
Core concepts of Artificial Intelligence (AI) and Generative AI (GenAI), including operational mechanisms, value propositions for public sector operations, and inherent limitations
Effective prompting strategies: establishing consistent input structures, defining constraints, and specifying output requirements
Iterative refinement: optimizing results through systematic feedback loops and precise instruction sets
Quality assurance and verification: implementing checklists, cross-referencing, assumption testing, traceability, and acceptance criteria
Standardization of deliverables: developing templates for technical memos, executive summaries, reports, and actionable task lists
Documentation and requirements management: drafting, revising, structuring, summarizing, and defining change and requirement specifications
Responsible usage and data security protocols: ensuring confidentiality, intellectual property protection, adherence to governance principles, and safe-use policies for government contexts
Practical exercises using realistic, anonymized scenarios
Day 2: Applied Scenarios, Productivity Enhancement, and Workflow Integration
Analysis and reporting: transforming raw data into structured insights and executive-ready summaries
Problem resolution and troubleshooting: leveraging AI for root cause analysis and action planning
Cross-functional communication: enhancing decision clarity, facilitating handovers, documenting meeting minutes, and aligning stakeholder expectations
AI as a development copilot: safely generating and reviewing code snippets, pseudocode, and test logic
Accelerating knowledge work: creating reusable procedures, internal standards, and knowledge-base content
Workflow integration: establishing repeatable end-to-end processes from request to final deliverable, including validation steps
Prompt libraries and checklists: implementing role-based collections to ensure consistency and broad adoption for government functions
Capstone exercise and 30-day adoption roadmap: translating individual practical cases into repeatable workflows, with an emphasis on rapid improvements and basic performance metrics
Requirements
This training is tailored for professionals operating in engineering, technical, and operational settings who manage documentation, structured processes, data-driven decision-making, and inter-team collaboration. It is appropriate for specialists and team leads seeking to enhance productivity and the quality of their outputs using 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 regularly engage with technical information and require clearer, faster, and more consistent deliverables for government operations.
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 !
