Goal: Make the fundamentals understandable without math or special hardware.

Topics

• How transformers work

• Tokenization & embeddings

• Attention mechanisms (visual demos)

• Fine-tuning vs prompting

• Retrieval-Augmented Generation (RAG)

• Inference vs training

• Why “bigger” doesn’t always mean “better”

Tools Used

• OpenAI Playground

• Gemini Playground

• Neet.ai transformer visualizer

• HuggingFace Spaces demo apps

Hands-On Activities

• Explore how attention layers highlight words

• Inspect how a model tokenizes different phrases

• Run small hosted models using HuggingFace Spaces

Goal: Teach practical, high-impact prompting skills. 

Topics

• How transformers work

• Tokenization & embeddings

• Attention mechanisms (visual demos)

• Fine-tuning vs prompting

• Retrieval-Augmented Generation (RAG)

• Inference vs training

• Why “bigger” doesn’t always mean “better”

Tools Used

• OpenAI Playground

• Gemini Playground

• Neet.ai transformer visualizer

• HuggingFace Spaces demo apps

Hands-On Activities

• Explore how attention layers highlight words

• Inspect how a model tokenizes different phrases

• Run small hosted models using HuggingFace Spaces

Goal: Show learners immediate, real-world value in daily workflows.

Topics

• Research and summarization

• Email drafting and documentation

• AI-assisted planning and decision support

• Enhancing sales, procurement, HR, and finance tasks

• AI for data analysis with browser-based tools

Tools Used

• ChatGPT, Claude, Gemini

• Google Workspace AI

• Whimsical, Notion AI

• PDF/Document analysis tools (AskYourPDF, ChatPDF)

Hands-On Activities

• Create an AI-assisted SOP

• Convert a long article into a structured report

• Build a personal “AI workflow” for a real task

Goal: Build responsible habits and critical thinking.

Topics

• Bias and hallucinations

• Security and privacy best practices

• Corporate and regulated environment considerations

• “Safe vs unsafe” prompting

• When not to use AI

Tools Used

• Any model with safety settings

• Online red-teaming guides

Hands-On Activities

• Identify safety risks in example prompts

• Red-team a prompt to stress-test model guardrails

• Rewrite risky prompts into safe alternatives

Goal: Let learners build functioning AI systems with zero code and zero compute.

Topics

• Simple AI agents

• Workflow automation

• Connecting AI to external tools

• Intro to APIs (conceptual)

• No-code RAG systems

• Designing effective assistants

Tools Used

• Make.com

• Zapier

• n8n (hosted options available)

• Replit Agents

• No-code RAG tools (Flowise Cloud, AskYourPDF+)

Hands-On Activities

• Build a simple task-running AI assistant

• Create a RAG chatbot using your own files

• Create a multi-step Make or Zapier automation

Goal: Provide lightweight coding exposure using browser-only tools.

Topics

• Python basics (browser notebooks)

• Using open models via API

• Running tiny models (1B–3B) using hosted inference

• Micro-fine-tuning demonstration

Tools Used

• Google Colab (free)

• HuggingFace Inference API

• Kaggle Notebooks

• Small models: LLaMA 3.2 1B, Phi-3 Mini, Gemma 2B

Hands-On Activities

• Build a simple text classifier

• Create a tiny AI-backed web app (Flask/FastAPI demo)

• Fine-tune a micro-model on a small dataset

Goal: Help leaders and teams adopt AI safely and strategically.

Topics

• AI maturity models

• Governance, risk, and policy frameworks

• AI implementation strategies

• Change management for AI rollout

• Workforce transformation

Tools Used

• Templates & worksheets

• AI strategy frameworks

• Governance checklists

Hands-On Activities

• Create an AI opportunity map

• Build a one-page AI strategy

• Draft an AI policy or guideline

• Instructor guide

• Slide decks

• Printable PDFs

• Step-by-step hands-on labs

• Templates & worksheets

• GitHub starter kit

• Assessment quizzes

• Certification exam