Course Outline
Day 1: Foundations and Reliable Use of GenAI
Understanding AI and Generative AI: core concepts, functionality, value propositions, and limitations
Effective prompting: utilising reusable prompt structures, clear inputs, constraints, and defined output formats
Refinement techniques: enhancing results through feedback loops and structured instructions
Ensuring output quality: employing checklists, cross-verification, managing assumptions, ensuring traceability, and meeting acceptance criteria
Standardising deliverables: developing templates for technical notes, summaries, reports, and action items
Documentation and requirements engineering: drafting, rewriting, structuring, summarising, and writing change/requirement specifications
Responsible usage and data security: maintaining confidentiality, protecting intellectual property, adhering to governance principles, and following safe-use protocols
Practical exercises using realistic, anonymised 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: 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: creating reusable procedures, internal standards, and knowledge-base content
Integrating workflows: establishing repeatable end-to-end processes from request to deliverable, including validation steps
Building prompt libraries and checklists: curating role-specific collections to enhance consistency and adoption
Capstone project and 30-day adoption plan: converting one practical case per participant into a repeatable workflow, focusing on quick wins and straightforward measurement
Requirements
This course is tailored for professionals in engineering, technical, and operational roles who manage documentation, structured processes, data-driven decision-making, and inter-team collaboration. It is ideal for specialists and team leaders seeking to boost productivity and output quality through the use of Generative AI in daily tasks, without necessitating advanced programming or data science expertise. The training is also valuable for operational and 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 !
