Course Outline
Day 1: Foundations and Reliable Use of GenAI
Essentials of AI and Generative AI: understanding capabilities, mechanisms, value propositions, and limitations
Practical prompting: utilizing reusable prompt structures, defining clear inputs, constraints, and output formats
Iteration techniques: refining outputs through feedback loops and structured instructions
Output quality and verification: applying checklists, cross-checking, 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 managing change/requirement writing
Responsible use and data security: maintaining confidentiality, protecting IP, adhering to governance principles, and following safe-use protocols
Hands-on practice using realistic, anonymized scenarios
Day 2: Applied Use Cases, Productivity, and Workflow Integration
Analysis and reporting: converting 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, drafting meeting minutes, and aligning stakeholders
AI as a copilot for code and automation: safely generating and reviewing code 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: building role-based collections to improve consistency and adoption
Capstone practice and 30-day adoption plan: transforming one practical case per participant into a repeatable workflow, highlighting quick wins and simple measurement metrics
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 seeking to boost productivity and output quality through Generative AI in their daily routines, with no prerequisite for advanced programming or data science skills. The course also benefits operational or business support personnel 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 !
