Classes in AI Literacy Course for Modern Workforces
 Module 1 — What AI Actually Is
Section 1: Plain-Language Definition
Section 3: Why AI Suddenly Matters
Section 4: No Hype, No Doom
 Module 2 — What AI Is Not
Section 1: AI Is Not Sentient
Section 2: Not always correct
Section 3: Not magic
 Module 3 — Generative AI 101
Section 1: Text generation
Section 2: Image/audio
Section 3: Embeddings
 Module 4 — How to Talk to an AI
Section 1: Examples vs instructions
Section 2: Personas
Section 3: Constraints
Section 4 : Iteration loops
 Module 5 — Email, Messaging, and Professional Tone
Section 1: Drafting
Section 2: Rewriting
Section 3: Tone styling
Section 4: Speeding Up Busywork
 Module 6 — Summarizing and Understanding Complex Stuff
Section 1: PDFs
Section 2: Long docs
Section 3: Meetings
Section 4: Rules & policies
Section 5: Accuracy expectations
 Module 7 — Data Safety & Common Mistakes
Section 2: No personal data
Section 3: What hallucinations look like
Section 4: How to double-check outputs
 Module 8 — Agentic AI: When AI Starts Taking Actions
Section 1: What agentic AI means
Section 2: Why it matters
Section 3: Practical examples
Section 4: Safety boundaries
 Module 9 — AI for Research (Without Getting Misled)
Section 1: Fact-checking
Section 2: Citing
Section 3: Evaluating Reliability
Section 4: Asking structured questions
 Module 10 — AI for Productivity
Section 1: Checklists
Section 2: Templates
Section 3: Brainstorming
Section 4: Project Planning
 Module 11 — AI Ethics in the Workplace
Section 1: Bias
Section 2: Equity
Section 3: Human-in-the-Loop
Section 4: Drafts vs Decisions
 Module 12 — AI and the Future of Work
Section 2: New Roles, New Skills
Section 3: What Companies Can Expect
 Module 13 — Where to Go Next
Section 1: Practice Sandbox
Section 2: Internal guidelines
Section 3: Example prompts