Course Outline
Day 1: Foundations and Reliable Use of GenAI
Key concepts of AI and GenAI: understanding functionality, value addition, and limitations
Effective prompting: utilizing reusable prompt structures, clear inputs, constraints, and defined output formats
Iteration methods: refining outputs through feedback loops and structured instructions
Ensuring output quality and verification: using checklists, cross-checking, managing assumptions, ensuring traceability, and defining acceptance criteria
Standardizing deliverables: creating templates for technical notes, summaries, reports, and action items
Documentation and requirements: techniques for drafting, rewriting, structuring, summarizing, and writing change/requirement documents
Responsible use and data security: maintaining confidentiality, protecting IP, applying governance principles, and following 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: 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
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
Prompt libraries and checklists: implementing role-based collections to enhance consistency and adoption
Capstone practice 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 targets 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 leaders seeking to boost productivity and output quality by integrating Generative AI into daily tasks, without needing advanced programming or data science expertise. The course is also beneficial for operational or business support roles that 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 !
