Course Outline
Day 1: Foundations and Reliable Use of GenAI
Core concepts of AI and Generative AI: understanding capabilities, mechanisms, value propositions, and limitations
Effective prompting: utilizing reusable prompt frameworks, defining clear inputs, setting constraints, and specifying output formats
Refinement techniques: improving results via feedback loops and structured instructions
Quality assurance and verification: employing checklists, cross-verification, identifying assumptions, ensuring traceability, and meeting acceptance criteria
Standardizing outputs: developing templates for technical notes, summaries, reports, and action items
Documentation and requirements management: drafting, rewriting, structuring, summarizing, and crafting change/requirement documents
Ethical usage and data security: maintaining confidentiality, protecting IP, adhering to governance principles, and following safe-use guidelines
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: clarifying decisions, managing handovers, recording meeting minutes, and aligning stakeholders
AI as a coding copilot: safely generating and reviewing code snippets, pseudocode, and test logic
Accelerating knowledge work: creating reusable procedures, internal standards, and knowledge base content
Integrating into workflows: establishing repeatable end-to-end processes from request to delivery, including validation steps
Leveraging prompt libraries and checklists: implementing role-specific collections to boost consistency and adoption
Capstone exercise and 30-day adoption strategy: converting one practical case per participant into a repeatable workflow, focusing on quick wins and simple metrics
Requirements
This course is tailored for professionals operating in engineering, technical, and operational environments who manage documentation, structured processes, data-informed decisions, and cross-team collaboration. It is ideal for specialists and team leaders seeking to boost productivity and output quality through the integration of Generative AI in routine tasks, with no advanced programming or data science background required. The training is also beneficial for operational and 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 !
