Course Outline
Day 1: Foundations and Reliable Use of GenAI
Key concepts of AI and GenAI: understanding its mechanics, value proposition, and limitations
Effective prompting: utilizing reusable prompt structures, defining clear inputs, setting constraints, and specifying output formats
Refinement techniques: enhancing results through iterative feedback and structured instructions
Quality assurance and verification: employing checklists, cross-verification, 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 specifying changes/requirements
Ethical usage and data security: maintaining confidentiality, protecting intellectual property, adhering to governance principles, and following safe-use guidelines
Practical exercises using 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 developing action plans
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
Workflow integration: establishing repeatable end-to-end processes from request to deliverable, including validation steps
Prompt libraries and checklists: curating role-based resources to boost consistency and adoption
Capstone exercise and 30-day adoption plan: converting one practical case per participant into a repeatable workflow, identifying quick wins, and establishing simple metrics
Requirements
This course is tailored for engineering, technical, and operational professionals who manage documentation, structured processes, data-driven decision-making, and team collaboration. It is ideal for specialists and team leaders aiming to boost productivity and output quality using Generative AI in their daily tasks, with no advanced programming or data science background required. The content is also pertinent for operational and business support roles that regularly engage with technical information and seek to produce clearer, faster, and more consistent results.
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 !
