Day 1 (2 Hours): Introduction to AI & Generative AI
Focus: Building curiosity and foundational understanding
Session 1: AI in the Real World (30 min)
- Icebreaker: “Where have you seen AI today?”
- What is Artificial Intelligence?
- Narrow AI vs. Generative AI (student-friendly examples)
- Myths vs. reality of AI
Session 2: How Generative AI Works (45 min)
Basics of:
- Neural networks (intuitive explanation)
- Training data & learning patterns
- Transformers & LLMs (conceptual, not math-heavy)
- Types of Generative AI:
- Text, image, music, video, code
Session 3: Hands-On + Ethics (45 min)
- Live demo: ChatGPT / Copilot / DALL·E
- Student activity:
- Write a poem, story, or summary
- Discussion:
- Bias
- Hallucinations
- Responsible AI usage
Learning Outcome:
Students understand what Generative AI is and where it is used.
Day 2 (2 Hours): Prompting & Creative Use of Generative AI
Focus: Using AI effectively
Session 1: Prompt Engineering Basics (30 min)
- What is a prompt?
Prompt structure:
- Role
- Task
- Context
- Output format
- Good vs. bad prompts
Session 2: Creative Applications (45 min)
Using AI for:
- Study assistance
- Content creation
- Coding help
- Resume & presentations
- Demo: Improving outputs using better prompts
Session 3: Student Activity (45 min)
Hands-on:
- Create a study guide
- Generate quiz questions
- Create social media content
- Peer review of outputs
Learning Outcome:
Students can write effective prompts and use AI productively.
Day 3 (2 Hours): OpenAI Tools & APIs (No-Code + Intro Code)
Focus: Understanding OpenAI ecosystem
Session 1: OpenAI Overview (30 min)
- OpenAI mission & impact
Tools:
- ChatGPT
- DALL·E
- Whisper
- Where APIs are used in real apps
Session 2: API Concepts (45 min)
What is an API?
- Tokens, requests, responses (visual explanation)
Demo:
- No-code AI tools OR
- Simple Python API call (optional)
Session 3: Mini Lab (45 min)
Build:
- Simple chatbot OR
- AI-powered Q&A system
- Group brainstorming:
- Campus use cases (library bot, placement helper)
Learning Outcome:
Students understand how AI tools are integrated into applications.
Day 4 (2 Hours): Agentic AI & Future Skills
Focus: What’s next in AI
Session 1: What is Agentic AI? (30 min)
Difference:
- Chatbot vs. AI Agent
- Examples:
- Auto-research agents
- Task-planning agents
- How agents make decisions
Session 2: Agentic Workflows (45 min)
Components:
- Tools
- Memory
- Planning
- Feedback loops
- Demo: Multi-step task handled by AI
Session 3: Ethics, Careers & Future (45 min)
- AI risks & governance
AI career paths:
- Prompt engineer
- AI product manager
- AI developer
- Student reflection activity
Learning Outcome:
Students understand Agentic AI and future AI career possibilities.
Optional Day 5 (2 Hours): Mini Project & Assessment
Focus: Applying knowledge
Group project:
- AI study assistant
- Campus chatbot
- AI content generator
- Presentation & feedback
- Quiz or reflection
