AI/ML Demos for Students, Faculty & Practitioners | Zero API Keys | Zero Server | 100% Classroom-Ready
Author: Professor Vinaya Sathyanarayana
GitHub: @VinayaSharada
Contact: vinallcontact@gmail.com
Get started in under 30 seconds:
# Browser Demos - No Installation Required
open TechUseCaseDemos/RAGSolutions/StandardRAG/index.html
# Python Demos
cd TechUseCaseDemos/Classification/demo001
pip install -r requirements.txt
python classificationdemo.pyWe follow a three-tier approach for AI model usage:
| Tier | Approach | Description | Examples |
|---|---|---|---|
| 🥇 1st Choice | Browser-based SLMs | Models running locally in browser | SmolLM2, DistilBERT, Whisper Tiny, all-MiniLM |
| 🥈 2nd Choice | Backend SLMs | Models downloaded and run locally | Phi-3.5, Mistral, Llama.cpp models |
| 🥉 3rd Choice | External LLM APIs | Cloud APIs only when no alternative | OpenAI, Anthropic, Google (last resort) |
Why this philosophy?
- ✅ Zero cloud required for 80%+ of demos
- ✅ No API keys needed for core functionality
- ✅ Privacy preserved - data stays local
- ✅ Cost effective - no per-token charges
| Metric | Value |
|---|---|
| Total Demos | 63+ |
| Browser-Based Demos | 44+ |
| Python Demos | 20+ |
| Courses Covered | 7 |
| Course | Demos | Key Topics |
|---|---|---|
| AI/ML Financial Services | 11+ | Banking, fraud, credit, wealth management, options, VaR |
| Management of AI Products | 16+ | Product strategy, risk, governance, RAG, financial analysis |
| Cyber Security | 7+ | IoT security, threat detection, penetration testing |
| NLP & Information Extraction | 16+ | Entity recognition, sentiment, RAG, voice assistants |
| Data Mining | 7 | Classification, clustering, forecasting, pattern mining |
| Wealth Management | 3+ | Portfolio theory, options pricing, NPV |
| Public Policy & Governance | 2 | Resource allocation, AI compliance |
New! AI Workflow Demos section in Management of AI Products catalog - perfect for showing AI value transformation
| Audience | What You Get |
|---|---|
| Students | Hands-on demos with step-by-step instructions, no cloud required |
| Faculty | Classroom-ready materials, assignment scaffolds, assessment rubrics |
| Practitioners | Real-world patterns, production-ready code, best practices |
| Demo | Model | Size | Use Case |
|---|---|---|---|
| Local Chat Advisor | SmolLM2-135M | 135 MB | Conversational AI |
| Smart Ticket Tagger | DistilBERT | 140 MB | Customer support |
| Whisper Voice Transcriber | Whisper Tiny | 39 MB | Speech-to-text |
| Semantic Search Engine | all-MiniLM | 23 MB | Document search |
| Demo | Type | Key Feature |
|---|---|---|
| Standard RAG | Text-based | Document upload + QA |
| Graph RAG | Graph-based | Knowledge traversal |
| Voice RAG | Voice-enabled | Speak + get answers |
| Emotional Support AI | Empathetic AI | Emotion detection |
| University Knowledge Assistant | Hybrid RAG | FalkorDB + PageIndex + Voice |
| Demo | Description | Theory | Learning Outcomes |
|---|---|---|---|
| Learning Resource Recommender | Traditional vs AI recommendations | Collaborative filtering, embeddings | Compare precision/recall, understand embedding spaces |
| Content Summarizer | Extractive vs abstractive summarization | NLP transformers, attention | Evaluate coherence vs factual accuracy |
| Data Analyzer | Statistical vs AI-powered analysis | Descriptive stats, anomaly detection | Interpret statistical vs narrative insights |
| Probabilistic Decision Engine | Amortized inference for predictions | Variational inference | Trade-offs between speed and accuracy |
| Demo | Description | Theory | Learning Outcomes |
|---|---|---|---|
| CopilotKit Agent Demo | Agentic workflows with streaming and tools | LLM function calling, orchestration | Build agentic applications with tool integration |
| Demo | Description | Theory | Learning Outcomes |
|---|---|---|---|
| Black-Scholes Option Pricer | European option pricing with Greeks | Black-Scholes-Merton calculus | Delta hedging, volatility impact |
| Monte Carlo Options | Simulation-based exotic option pricing | Monte Carlo, risk-neutral valuation | Convergence, variance reduction |
| Risk Parity Portfolio | Equalize risk contribution | Risk parity theory | Optimize risk allocation |
| VaR Calculator | Value at Risk with Expected Shortfall | Parametric/Historical simulation | Tail risk, regulatory capital |
| Greeks Calculator | Delta, Gamma, Vega, Theta sensitivity | Option sensitivity measures | Hedge positions, manage risk |
| Counterparty Risk | CVA/DVA calculations | Credit valuation adjustment | Counterparty risk, expected exposure |
| Bond Pricing | Bond pricing with duration | Present value of cash flows | Yield, duration, premium/discount |
| Bank Failure Prediction | Predict bank failures using financial ratios | Credit risk, logistic regression | |
| Options Pricing | Options pricing with Greeks | Black-Scholes-Merton calculus |
KateelLearningDemosToStudents/
├── 🤖 Browser-AI-Demos/ # Zero-cloud AI apps
├── DomainUseCaseDemos/ # Industry verticals (Finance, Banking)
├── TechUseCaseDemos/ # Technique-first ML demos
├── CourseCatalogs/ # Structured course materials
├── Assignments/ # Ready-to-use assignments
└── ecomm001/ # E-commerce analytics pipeline
- ✅ No cloud required - Many demos run entirely in browser
- ✅ No API keys - Local models only
- ✅ Production patterns - Real-world best practices
- ✅ Active maintenance - New demos monthly
- ✅ Educational focus - Theory + hands-on learning
Email for course adoption: vinallcontact@gmail.com
Subject format: [KateelLearningDemos] Usage - <Your Name/Institution>
Educational Use - Free for students, faculty, and practitioners.
Attribution required - Include citation in presentations/publications.
Demos and course material adapted from the KateelLearningDemosToStudents repository
by Professor Vinaya Sathyanarayana
GitHub Repository
If you find this repository helpful, please consider:
- ⭐ Starring the repository
- 🍴 Forking and contributing
- 📧 Reaching out for collaboration opportunities
Last Updated: June 2026 | Total Demos: 63+