Course Outline
Foundations and Reliable Use of GenAI
- Core concepts of AI and GenAI: definitions, mechanics, value addition, and limitations
- Practical prompting: reusable structures, clear inputs, constraints, and output specifications
- Iteration methods: refining outcomes through feedback loops and structured guidance
- Output quality and verification: checklists, cross-referencing, assumption tracking, traceability, and acceptance criteria
- Standardizing deliverables: templates for technical notes, summaries, reports, and action items
- Documentation and requirements: drafting, revising, structuring, summarizing, and writing change/requirement specifications
- Responsible use and data security: confidentiality, IP protection, governance principles, and safe handling rules
- Practical exercises using realistic, anonymized scenarios
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
- Cross-functional communication: clarifying decisions, managing handovers, documenting meeting minutes, and aligning stakeholders
- AI as a coding copilot: safe generation and review of code snippets, pseudocode, and test logic
- Accelerating knowledge work: creating 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: converting one practical case per participant into a repeatable workflow, focusing on quick wins and simple metrics
Requirements
This course targets professionals in engineering, technical, and operational settings who manage documentation, structured workflows, data-driven decision-making, and inter-team collaboration. It is ideal for specialists and team leaders seeking to boost productivity and enhance output quality by integrating Generative AI into their routine activities, without needing advanced programming or data science expertise. Additionally, the content is highly relevant for business support and operational roles that regularly process technical information and require clear, rapid, and standardized 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 !