Course Outline
Foundations and Reliable Use of GenAI
- AI and GenAI essentials: understanding capabilities, mechanics, value-add scenarios, and limitations
- Practical prompting: constructing reusable prompt structures, defining clear inputs, constraints, and output formats
- Iteration techniques: refining outputs through feedback loops and structured instruction sets
- Output quality and verification: utilizing checklists, cross-referencing, assumption analysis, traceability, and acceptance criteria
- Standardizing deliverables: creating templates for technical notes, summaries, reports, and action items
- Documentation and requirements: drafting, rewriting, structuring, summarizing, and authoring change or requirement documents
- Responsible use and data security: managing confidentiality, IP protection, governance principles, and safe-use protocols
- Hands-on practice using realistic, anonymized scenarios
Applied Use Cases, Productivity, and Workflow Integration
- Analysis and reporting: transforming raw inputs into structured insights and executive-ready summaries
- Problem solving and troubleshooting: conducting AI-supported root cause analysis and action planning
- Cross-functional communication: enhancing decision clarity, managing handovers, documenting meeting minutes, and aligning stakeholders
- 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: curating role-based collections to enhance consistency and adoption
- Capstone practice and 30-day adoption plan: converting a practical case study per participant into a repeatable workflow, focusing on quick wins and simple metrics
Requirements
This training is tailored for professionals operating within engineering, technical, and operational settings who regularly manage documentation, structured processes, data-informed decisions, and cross-team collaboration. It is ideal for specialists and team leaders seeking to elevate productivity and output quality by leveraging Generative AI in routine tasks, with no prior advanced programming or data science background required. The course also provides significant value for operational and 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 !
