Course Outline
Day 1: Foundations and Reliable Use of GenAI
Understanding AI and Generative AI: core concepts, functionality, value proposition, and limitations
Effective prompting: constructing reusable prompt frameworks, defining clear inputs, setting constraints, and specifying output formats
Iterative refinement: improving results through feedback loops and structured instructions
Ensuring output quality and verification: utilizing checklists, cross-referencing, identifying assumptions, maintaining traceability, and defining acceptance criteria
Standardizing deliverables: creating templates for technical notes, summaries, reports, and action items
Documentation and requirements management: techniques for drafting, rewriting, structuring, summarizing, and writing change/requirement specifications
Responsible usage and data security: principles of confidentiality, intellectual property protection, governance, and safe-use protocols
Practical exercises using realistic, anonymized scenarios
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
Enhancing cross-functional communication: improving decision clarity, handovers, meeting minutes, and stakeholder alignment
AI as a copilot for code and automation: safely generating and reviewing code snippets, pseudocode, and test logic
Accelerating knowledge work: developing reusable procedures, internal standards, and knowledge-base content
Integrating workflows: establishing repeatable end-to-end processes from request to delivery, including validation steps
Building prompt libraries and checklists: creating role-based 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 simple metrics
Requirements
Tailored for professionals in engineering, technical, and operational roles who manage documentation, structured processes, data-driven decision-making, and team collaboration, this training is ideal for specialists and team leaders seeking to boost productivity and output quality through Generative AI. No advanced programming or data science background is required. The course is also highly relevant 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 !
