Course Outline
Day 1: Foundations and Reliable Use of GenAI
AI and GenAI essentials: understanding core concepts, functionality, value propositions, and limitations
Practical prompting: utilizing reusable prompt structures, clear inputs, constraints, and defined output formats
Iteration techniques: refining outcomes through feedback loops and structured instructions
Output quality and verification: employing checklists, cross-checking methods, identifying assumptions, ensuring traceability, and meeting acceptance criteria
Standardizing deliverables: creating templates for technical notes, summaries, reports, and action items
Documentation and requirements: techniques for drafting, rewriting, structuring, summarizing, and specifying changes/requirements
Responsible use and data security: maintaining confidentiality, protecting intellectual property, adhering to governance principles, and following safe-use protocols
Hands-on practice with 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: utilizing AI-supported root cause analysis and action planning
Cross-functional communication: enhancing decision clarity, managing handovers, recording meeting minutes, and aligning stakeholders
AI as a copilot for code and automation: safely generating and reviewing snippets, pseudocode, and test logic
Knowledge work acceleration: 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: compiling role-based collections to improve consistency and adoption
Capstone practice and 30-day adoption plan: converting one practical case per participant into a repeatable workflow, identifying quick wins and simple measurement metrics
Requirements
This training is tailored for professionals operating in engineering, technical, and environmental roles who manage documentation, structured processes, data-driven decision-making, and cross-team collaboration. It is particularly beneficial for specialists and team leads seeking to enhance productivity and output quality through the integration of Generative AI into routine tasks, without necessitating advanced programming or data science expertise. The content is also highly relevant for operational and business support roles that frequently engage with technical information, aiming to produce 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 !
