Four Tiers of AI Education. One Continuous Journey.
From a Class 3 student building their first chatbot in Scratch to a PhD researcher training transformers on GPU clusters — the AI VIDYA curriculum is a single, coherent learning pathway aligned with NEP 2020, CBSE, AICTE, and NSDC frameworks.
एआई विद्या — ज्ञान से नवाचार तक
Learning Progression
How the curriculum is built
Every module follows these four principles — ensuring students don't just learn about AI, they build with it.
Modular
Institutions can adopt the complete package or select specific modules. Each module stands alone while building toward the full tier.
Hands-On
Every module includes practical projects. Students build chatbots, classifiers, models, and real-world applications — not just answer MCQs.
Age-Appropriate
Tier A uses visual tools (Scratch, Teachable Machine). Tier B introduces Python. Tier C uses GPU-level frameworks. Tier D focuses on trade tools.
Board-Aligned
Mapped to CBSE SOAR, NCF-SE 2023, CISCE Robotics & AI, AICTE BTech AI/ML, and NSDC Qualification Packs.
AI Foundations
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This tier introduces students to computational thinking, basic AI concepts, and hands-on experimentation through age-appropriate, visual, and gamified content. Students learn by doing — building chatbots, image classifiers, and simple games — not by memorizing definitions.
| Module | What Students Learn | Tools & Software |
|---|---|---|
| Computational Thinking | Algorithms, pattern recognition, decomposition, sequencing, flowcharts | Scratch, Blockly, Unplugged activities |
| Introduction to AI | What AI is, how machines learn, AI in everyday life, AI vs. humans | Google Teachable Machine, PictoBlox |
| Data Awareness | What is data, types of data, collecting and organizing data, basic charts | Google Sheets, Excel basics, Kaggle datasets |
| AI Ethics & Safety | Responsible AI use, bias awareness, digital citizenship, privacy | Interactive scenarios, case studies |
| Mini Projects | Build a chatbot, image classifier, voice assistant, smart game | Scratch AI extensions, MIT App Inventor |
AI Chatbot
Build a conversational chatbot using Scratch AI extensions that answers questions about a chosen topic
Image Classifier
Train Google Teachable Machine to recognize hand gestures, animals, or everyday objects
Smart Game
Create a Scratch game where the AI opponent learns from the player's moves
AI Applications
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Students transition from visual tools to Python and real AI/ML frameworks. They build working machine learning models, explore computer vision and NLP, and complete an end-to-end capstone project — from problem identification to working demo.
| Module | What Students Learn | Tools & Software |
|---|---|---|
| Python for AI | Python basics, data structures, loops, functions, NumPy, Pandas | Python 3.x, Jupyter Notebooks, VS Code |
| Machine Learning Basics | Supervised/unsupervised learning, decision trees, regression, classification | scikit-learn, Orange Data Mining |
| Computer Vision | Image processing, object detection, face recognition, OCR | OpenCV, TensorFlow Lite, YOLO |
| Natural Language Processing | Text processing, sentiment analysis, chatbots, translation | NLTK, spaCy, Hugging Face (basic) |
| AI for Social Good | Healthcare AI, agriculture AI, climate AI, accessibility tools | Project-based: real-world problem solving |
| Capstone Project | End-to-end AI project: problem identification to deployment | Full stack: data collection to demo |
Health Predictor
Build a model that predicts diabetes risk from patient data using decision trees and logistic regression
Crop Disease Detector
Train a computer vision model to identify plant diseases from leaf images using OpenCV
Sentiment Analyzer
Build an NLP pipeline that analyzes product review sentiment using NLTK and visualizes results
AI Engineering
This is where students become AI engineers. Deep learning, generative AI, MLOps, and AI infrastructure — all on GPU-accelerated hardware. Students train real models, fine-tune LLMs locally, containerize deployments, and produce original research.
| Module | What Students Learn | Tools & Software |
|---|---|---|
| Deep Learning | Neural networks, CNNs, RNNs, transformers, GANs, training at scale | PyTorch, TensorFlow, CUDA, RDP GPU Workstations |
| Generative AI | LLMs, prompt engineering, fine-tuning, RAG, multi-modal AI | Ollama, LangChain, Hugging Face, Open-source LLMs |
| MLOps & Deployment | Model versioning, CI/CD for ML, containerization, edge deployment | Docker, MLflow, FastAPI, RDP Edge PCs |
| AI Infrastructure | GPU computing, distributed training, data pipelines, cloud vs. on-prem | RDP AI Servers, Kubernetes, NVIDIA tools |
| Domain AI Labs | AI for Healthcare, Finance, Manufacturing, Agriculture, NLP for Indian languages | Domain-specific datasets and frameworks |
| Research Project | Original research, paper writing, conference presentation | Full lab access: GPU Workstations + AI Servers |
Fine-Tuned LLM
Fine-tune an open-source LLM on a domain-specific Indian language dataset using Ollama and LoRA
Defect Detection System
Build a real-time quality inspection pipeline using YOLO on a GPU workstation with live camera feed
ML Pipeline Deployment
Containerize an ML model with Docker, version with MLflow, serve via FastAPI, and deploy to edge
AI Skills
Practical, trade-aligned AI training that makes graduates immediately employable. Not computer science theory — real AI tools for real jobs. Students learn to use AI assistants, automate workflows, apply AI to their trades, and even freelance using AI.
| Module | What Students Learn | Tools & Software |
|---|---|---|
| Digital Literacy + AI Awareness | Computer basics, internet, AI tools for productivity, ChatGPT usage, Copilot for daily tasks | Windows 11, Office 365, Copilot, ChatGPT |
| AI-Powered Tools for Trades | AI in manufacturing, AutoCAD AI, predictive maintenance, quality control, trade-specific applications | Trade-specific AI tools, simulation software |
| Data Entry & AI Automation | Data handling, basic automation, RPA concepts, AI-assisted workflows, Excel automation | Excel, Power Automate, basic Python scripts |
| AI Entrepreneurship | Using AI to start businesses, AI freelancing, prompt engineering as a skill, AI content creation | Canva AI, ChatGPT, AI writing/design tools |
Predictive Maintenance Alert
Build an Excel-based alert system that predicts machine failure from vibration sensor data
AI Business Portfolio
Create a complete freelance portfolio using Canva AI, ChatGPT, and AI writing tools
Workflow Automation
Automate a data entry workflow using Power Automate with email triggers and Excel output
Mapped to every major education framework
राष्ट्रीय शिक्षा नीति के अनुरूप
The AI VIDYA curriculum doesn't exist in isolation. Every tier is mapped to the frameworks that matter — so your institution can adopt it with confidence.
| Tier | Primary Alignment | Secondary Alignment | Certification Maps To |
|---|---|---|---|
| Tier A | CBSE SOAR Module, NCF-SE 2023 | NCERT AI Curriculum, KVS Digital Literacy | RDP AI Explorer |
| Tier B | CBSE AI Elective (083), CISCE Robotics & AI | NTA JEE CS syllabus, State Board CS electives | RDP AI Practitioner |
| Tier C | AICTE BTech AI/ML curriculum | UGC NET AI syllabus, ACM CS2023 | RDP AI Professional |
| Tier D | NSDC Qualification Packs, NCVET Levels | Skill India Digital, State Skill Mission standards | RDP AI Skills Ready |
Ready to bring this curriculum to your institution?
The curriculum is pre-loaded on every RDP AI PC and comes with teacher training, student workbooks, and certification. Pick the right tier for your students and let's get started.
Indian curriculum. Indian frameworks. Built by a Make-in-India OEM.