Course Outline
Day 1: Foundations and Reliable Use of GenAI
Essentials of AI and Generative AI: understanding capabilities, limitations, and value propositions
Effective prompting: utilizing reusable prompt structures, defining clear inputs, constraints, and output formats
Iteration strategies: refining outputs through feedback loops and structured instructions
Ensuring output quality and verification: using checklists, cross-referencing, managing assumptions, ensuring traceability, and defining acceptance criteria
Standardizing deliverables: creating templates for technical notes, summaries, reports, and action items
Documentation and requirements engineering: techniques for drafting, rewriting, structuring, summarizing, and writing change/requirement specifications
Responsible usage and data security: principles of confidentiality, IP protection, governance, and safety rules
Hands-on exercises using realistic, anonymized scenarios
Day 2: Applied Use Cases, Productivity, and Workflow Integration
Analyzing and reporting: transforming raw data 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
Integrating workflows: establishing repeatable end-to-end processes from request to delivery, including validation steps
Prompt libraries and checklists: assembling role-based collections to improve consistency and adoption rates
Capstone project and 30-day adoption plan: converting one practical case per participant into a repeatable workflow, focusing on quick wins and simple measurement metrics
Requirements
Designed for engineering, technical, and operational professionals who manage documentation, structured processes, data-driven decisions, and cross-team collaboration, this training is ideal for specialists and team leads seeking to boost productivity and output quality through everyday Generative AI use. No advanced programming or data science background is required. The course also benefits 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 !
