Course Outline
Day 1: Foundations and Reliable Use of GenAI
AI and GenAI essentials: understanding its functionality, value addition, and limitations
Practical prompting: utilizing reusable prompt structures, clear inputs, constraints, and output formats
Iteration techniques: refining outcomes through feedback loops and structured instructions
Output quality and verification: employing checklists, cross-checking, handling assumptions, traceability, and acceptance criteria
Standardizing deliverables: templates for technical notes, summaries, reports, and action items
Documentation and requirements: drafting, rewriting, structuring, summarizing, and writing change/requirement specifications
Responsible use and data security: confidentiality, IP protection, governance principles, and safe-use guidelines
Hands-on practice with 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: AI-supported root cause analysis and action planning
Cross-functional communication: ensuring decision clarity, effective handovers, meeting minutes, and stakeholder alignment
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: role-based collections to enhance consistency and adoption
Capstone practice and 30-day adoption plan: transforming 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 fields who manage documentation, structured processes, data-driven decisions, and team collaboration. It is ideal for specialists and team leads seeking to boost productivity and output quality through Generative AI in their routine tasks, without the need for advanced programming or data science expertise. The course is also beneficial for operational or 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 !
