Course Outline
Day 1: Foundations and Reliable Use of GenAI
Core concepts of AI and Generative AI: understanding functionality, value creation, and limitations
Effective prompting: utilizing reusable structures, precise inputs, constraints, and defined output formats
Refinement techniques: enhancing results through iterative feedback loops and structured guidance
Quality assurance and verification: employing checklists, cross-referencing, managing assumptions, ensuring traceability, and defining acceptance criteria
Standardizing outputs: creating templates for technical notes, summaries, reports, and action items
Documentation and requirements engineering: drafting, revising, structuring, summarizing, and specifying requirements
Ethical use and data security: maintaining confidentiality, protecting IP, adhering to governance principles, and following safe-use guidelines
Practical exercises using realistic, anonymized case studies
Day 2: Applied Use Cases, Productivity, and Workflow Integration
Analysis 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
Cross-functional communication: enhancing decision clarity, streamlining handovers, documenting meeting minutes, and aligning stakeholders
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 resources
Workflow integration: establishing repeatable end-to-end processes from request to delivery, including validation steps
Prompt libraries and checklists: implementing role-specific collections to improve consistency and adoption
Capstone exercise and 30-day implementation plan: converting one practical case per participant into a repeatable workflow, identifying quick wins and establishing simple metrics for success
Requirements
This training is tailored for professionals operating in engineering, technical, and business environments who manage documentation, structured processes, data-driven decisions, and team collaboration. It is ideal for specialists and team leaders seeking to boost productivity and output quality using Generative AI in daily tasks, without necessitating advanced programming or data science expertise. The course also benefits operational or administrative support staff who regularly 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 !
