Module 1 – Introduction to Generative AI
What will you Learn?
- What is Generative AI? (vs. Traditional AI)
- Types: Text, Image, Audio, Video, Multimodal
- Key Players: OpenAI, Anthropic, Stability AI, Google DeepMind
- Real-world applications: marketing, healthcare, education, art
Practical Activity:
- Live demo: Ask ChatGPT to generate a blog post & an image using DALL·E.
- Group discussion: “Where can Generative AI be used in your industry?”
Cheat Sheet:
- AI Terminology: LLM, Prompt, Token, Diffusion, API
Module 2 – Understanding Large Language Models (LLMs)
What will you Learn?
- Architecture basics (Transformers, Attention mechanism)
- How LLMs are trained
- Popular models: GPT-4o, LLaMA 3, Claude 3.5, Gemini
- ChatGPT vs. API models vs. open-source models
Practical Activity:
- Use OpenAI Playground to test different prompts.
- Compare outputs from GPT-3.5 vs GPT-4.
Cheat Sheet:
- LLM Families & strengths
Module 3 – Image Generation
What will you Learn?
- How diffusion models work (Stable Diffusion, Midjourney, DALL·E)
- Use cases: Art, advertising, product design
- Image prompt structure: Subject + Style + Details + Lighting
Practical Activity:
- Create a poster for a college event using Midjourney or DALL·E.
- Experiment with “image-to-image” feature.
Cheat Sheet:
- Image prompt formula examples
Module 4 – Audio & Video Generation
What will you Learn?
- AI voice cloning (ElevenLabs)
- Music generation (Suno AI)
- AI video tools: RunwayML, Pika Labs, OpenAI Sora
Practical Activity:
- Create a short AI-generated product promo video.
- Clone your own voice and make an AI narration.
Cheat Sheet:
- List of Free & Paid AI media tools
Module 5 – Prompt Engineering
What will you Learn?
- What is prompt engineering?
- Types of prompts: Zero-shot, Few-shot, Role-play, Chain-of-Thought
- Writing better prompts for consistent results
Practical Activity:
- Improve a bad prompt step-by-step until the output becomes perfect.
- Group challenge: Best ad copy with a single prompt.
Cheat Sheet:
- 20 ready-to-use prompts for text, image, and code
Module 6 – Hands-on with APIs & Tools
What will you Learn?
- OpenAI API basics (authentication, requests, responses)
- Hugging Face model hub
- LangChain for AI workflow automation
Practical Activity:
- Connect OpenAI API to a Google Sheet to answer questions.
- Deploy a Hugging Face chatbot on the web.
Cheat Sheet:
- API request format + sample code (Python/JavaScript)
Module 7 – Fine-tuning & Custom Models
What will you Learn?
- Fine-tuning vs. Prompt-tuning
- LoRA fine-tuning process
- Dataset preparation & cleaning
Practical Activity:
- Fine-tune an open-source model on custom data (small dataset).
- Deploy it on Hugging Face Spaces.
Cheat Sheet:
- Fine-tuning workflow diagram
Module 8 – AI Automation & Agents
What will you Learn?
- What is an AI agent?
- Connecting AI to external tools (email, CRM, databases)
- Using Zapier/Make for AI automation
Practical Activity:
- Build an AI that sends automated LinkedIn messages.
- AI that extracts insights from PDF files.
Cheat Sheet:
- Popular AI agent frameworks & use cases
Module 9 – Ethics, Copyright & Legal Issues
What will you Learn?
- Risks: Bias, misinformation, misuse
- AI & copyright laws
- Guidelines for responsible AI use
Practical Activity:
- Group discussion: Should AI-generated art be allowed in competitions?
- Case study: Deepfake misuse
Cheat Sheet:
- AI Ethics Dos & Don’ts
Module 10 – Capstone Projects
Project Ideas:
- AI-powered customer support chatbot
- AI poster and video generator for events
- Resume & cover letter AI assistant
- AI social media content planner
Extra Resources for Students
- Tools List: ChatGPT, Midjourney, DALL·E, RunwayML, ElevenLabs, Suno, Hugging Face, LangChain