Course Outline
Day 1: Foundations and Reliable Use of GenAI
Core concepts of AI and GenAI: understanding functionality, value propositions, and limitations
Effective prompting techniques: utilizing reusable prompt structures, defining clear inputs, applying constraints, and specifying output formats
Iteration strategies: refining outcomes through feedback loops and structured instructions
Ensuring output quality and verification: employing checklists, cross-verification, identifying assumptions, ensuring traceability, and meeting acceptance criteria
Standardizing deliverables: developing templates for technical notes, summaries, reports, and action items
Documentation and requirements engineering: drafting, revising, structuring, summarizing, and writing change/requirement specifications
Responsible usage and data security: maintaining confidentiality, protecting IP, adhering to governance principles, and following safe-use guidelines
Practical application 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
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: creating reusable procedures, internal standards, and knowledge-base content
Integrating into workflows: establishing repeatable end-to-end processes from request to deliverable, including validation steps
Building prompt libraries and checklists: implementing role-based collections to enhance consistency and adoption
Capstone exercise and 30-day adoption plan: converting one practical case per participant into a repeatable workflow, focusing on quick wins and simple measurement
Requirements
This training is tailored for professionals in engineering, technical, and operational settings who manage documentation, structured processes, data-driven decision-making, and inter-team collaboration. It is ideal for specialists and team leads aiming to boost productivity and output quality by integrating Generative AI into routine tasks, with no prerequisite for advanced programming or data science expertise. The course also benefits 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 !
