MERN, JavaScript, DSA, AI engineering, AWS, UI/UX, project building, and system design —
one path, real projects, no fluff.
Eight tracks, all live. Each one ends with a real certificate.
From variables to closures, promises, and modern ES6+ patterns — the language behind everything else here.
You'll build: small interactive projects that lock in each concept as you go.
Pattern-based problem solving — arrays, trees, graphs, and dynamic programming, taught for interviews.
You'll build: a personal problem-solving playbook you can reuse in any interview.
MongoDB, Express, React and Node — how a full-stack web app actually fits together in production.
You'll build: a full-stack app with auth, a database, and a deployed frontend.
RAG pipelines, LLM app patterns, and voice AI — how we build the AI features inside DigitalAIIndia itself.
You'll build: a real RAG pipeline and a voice AI integration, end to end.
High-level and low-level design — how to structure a growing product so it doesn't fall over.
You'll build: HLD/LLD diagrams for a system that's designed to scale.
Hierarchy, type, contrast, spacing and states — design as rules you can apply, not taste you either have or don't.
You'll build: a real project of yours, redesigned and made accessible.
IAM, EC2, VPC, Docker, ECS Fargate, Lambda, EventBridge, S3, RDS and CodeArtifact — the services that actually matter, step by step.
You'll build: a containerised app running on AWS, with a teardown checklist.
Turn what you've learned into something real — planned, built, deployed, and documented like a shipped product.
You'll build: a portfolio-ready project, deployed and documented.
Every track fits into the same journey — skip ahead if you already know a stage.
Most tutorials teach syntax. We show how real products get built and shipped.
A preview of the AI engineering track — pulled straight from our own codebase. More tracks are being written.
from langchain_experimental.text_splitter import SemanticChunker from langchain_openai import OpenAIEmbeddings # Split on meaning, not character count splitter = SemanticChunker( OpenAIEmbeddings(), breakpoint_threshold_type="percentile" ) chunks = splitter.create_documents([document_text])
Intel × CBSE, under India's Digital India digital-literacy initiative
Completed 11 August 2026 · Abhishek Dandriyal, Founder
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