Course Outline
Day 1: Foundations and Reliable Use of GenAI
Essentials of AI and GenAI: understanding the fundamentals, functionality, value proposition, and limitations
Practical prompting: utilizing reusable prompt structures, defining clear inputs, constraints, and output formats
Iteration techniques: refining outputs through feedback loops and structured instructions
Output quality and verification: implementing checklists, cross-checking, identifying 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 specifications
Responsible use and data security: principles of confidentiality, IP protection, governance, and safe-use protocols
Hands-on practice with 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
Cross-functional communication: enhancing decision clarity, managing 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
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: creating role-based collections to improve consistency and adoption
Capstone practice and 30-day adoption plan: converting one practical case per participant into a repeatable workflow, highlighting quick wins and simple measurement methods
Requirements
This training is tailored for professionals operating in engineering, technical, and business environments who manage documentation, structured processes, data-informed decisions, and inter-team collaboration. It is particularly beneficial for specialists and team leaders seeking to enhance productivity and output quality through the use of Generative AI in routine tasks, without the need for advanced programming or data science expertise. The course is also relevant 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 !
