📚 Learn every concept behind OpenBenchML
A massive, hierarchical learning centre that teaches every concept used to build this platform — from Python variables and loops all the way to FastAPI routes, WebSocket broadcasting, sandboxed kernels, and CSS Grid. Every concept page has a runnable code snippet, a plain-English explanation, and a "where it's used" pointer back into the codebase.
Student Performance Predictor — 12 stages
Python → ML → FastAPI → Jinja → HTML. Concept, tiny task, check, next.
Edit code & see live output
CSS box-shadow 2px → 10px & see it change. Python, HTML, CSS, FastAPI labs.
Build OpenBenchML — Step by Step
A 10-step course that builds OpenBenchML from scratch. Each step teaches one concept and adds one feature. By step 10, you have a deployed app.
Python
The language the entire backend (and most of the frontend helpers) is written in. Start here if you're new.
Web & FastAPI
How HTTP requests become HTML pages and JSON responses.
Databases & SQL
How data survives between requests — tables, rows, sessions, migrations.
Machine Learning
The whole point of the platform — train, evaluate, rank models.
Frontend
HTML, CSS, and vanilla JS — the building blocks of every page.
Security
Authentication, authorisation, sandboxing, and the constant vigilance mindset.
DevOps & Deployment
From git push to live URL — Docker, Render, env vars, health checks.
Real-time & WebSockets
Pushing updates to browsers without polling — the magic behind live leaderboards.
Algorithms & Data Structures
The patterns that make code fast: hashing, sorting, recursion, complexity.
Mini Projects
Complete, runnable mini-projects that tie frontend + FastAPI + Docker + ML together. Each project has multiple files and a step-by-step explanation.