Mastery Path

A free, structured, module-wise training library

98 courses 3,600+ lessons 15 categories $0 cost, always

Mastery Path is a collection of 98 free, self-paced courses — one per language, platform or discipline — built and maintained by Vinod Bhanuja. Every course follows the same shape: Level 1 through Level 4, each level made of short topic modules with runnable examples, and a hands-on project that ties the level together. There's no signup and no paywall; pick a track below and start at Level 1.

Coverage spans programming languages (Python, Java, Go, Rust, TypeScript and 14 more), cloud platforms, AI/ML and LLM development, data engineering and analytics, embedded systems, security, testing/QA, DevOps infrastructure, and product/engineering leadership — see the full index below.

— Vinod Bhanuja

🎥 Prefer video? Watch the Mastery Path video series on YouTube — Shorts and full walkthroughs of these lessons.

"Structured enough to finish. Deep enough to matter."

— why every course here follows the same four levels

Popular starting points

Learning tracks — curated sequences across courses, by goal

🌐
Full-Stack Web Developer
Ship a complete web app, frontend to backend.
☁️
Cloud & DevOps Engineer
Containerize, orchestrate, and ship to production.
🛠️
Data Engineer
Build pipelines that move and shape real data.
🤖
AI / ML Engineer
Go from math foundations to shipping AI agents.
🧪
QA / SDET
Automate testing across the modern web stack.
🛡️
Security Engineer
Think like an attacker, build like a defender.
💻 Languages 20 20 languages, start to finish.
🌐 Web Frameworks 11 Build and ship on the modern web stack.
📱 Mobile 2 Native and cross-platform app development.
🧪 Testing & QA 6 Automated testing across languages and stacks.
🛡️ Security 2 Defense and offense, hands-on.
☁️ Cloud Platforms 5 AWS, Azure, GCP and more, from first principles.
📊 Data & Analytics 7 Pipelines, warehousing, and real-world analysis.
🗄️ Databases 5 Relational, document, cache, and lakehouse.
🤖 AI / ML / LLM 11 Models, agents, and applied ML engineering.
🔧 Embedded Systems 5 Firmware, RTOS, and hardware-close code.
🧭 Leadership & Management 5 Product, project, and people leadership.
🗣️ Professional Skills 2 Communication and workplace fluency.
🏆 Careers & Interviews 2 Interview and career prep that works.
🔗 Process & APIs 3 Agile delivery and API design in practice.
⚙️ Infrastructure & Ops 12 Containers, CI/CD, and running it in prod.