What you’ll learn
- Understand the fundamental mechanics of generative AI models and text generation probability.
- Identify and prevent data privacy violations, avoiding input of sensitive customer or proprietary data into unapproved public models.
- Transition personal daily workflows from unapproved free tools ("Shadow IT") to secure enterprise platforms.
How the course runs
Before the session
Pre-session prep · about 30 minutes
Complete a 15-minute diagnostic self-assessment on baseline AI understanding and review the corporate Acceptable Use Policy (AUP).
Live session
Instructor-led · 90 minutes
90-minute interactive workshop covering LLM boundary testing, data anonymisation techniques, and baseline prompt structure.
After the session
Practice & reinforcement
Execute Monday daily task practice—draft replies to 3 routine emails using context-rich briefs within 20 minutes.
Course modules
Introduction to Generative AI
Text prediction, limitations, and hallucination mechanics.
Data Safety & Privacy Guidelines
PII masking, client confidentiality, and enterprise opt-out policies.
Enterprise vs. Public AI Tools
Risk profiles of consumer ChatGPT vs. Enterprise Copilot/Claude.
Initial Interface Mastery
Navigating chat interfaces, parameter sliders, and system prompts.
What you’ll take away
Deliverable: Anonymised prompt template for daily email drafting.
How your learning is checked: Level 1 Knowledge Acquisition Quiz (100% mastery required on data security items).