Getting Started
Welcome to Quantum Resources, an open, community-driven learning hub for quantum computing. Whether you are a curious student, a software engineer pivoting into quantum, a researcher, or an AI practitioner exploring quantum machine learning, this site gives you a structured path through one of the most exciting fields in science and technology.
What you'll find here
| Section | What it gives you |
|---|---|
| 🗺️ Learning Roadmaps | Four structured paths — Beginner, Intermediate, Advanced, and Quantum AI. |
| 🧪 Hands-on Labs | Runnable tutorials: RNG, teleportation, Grover, Deutsch–Jozsa, a QML classifier. |
| 🧰 Frameworks | Getting-started guides for Qiskit, Cirq, PennyLane, Q#, Braket and TFQ. |
| 📚 Resources | 500+ curated books, courses, papers, videos and tools. |
| ⚛️ Interactive Tools | Bloch sphere, gate visualizer and circuit builder — all in your browser. |
| 💼 Career Paths | Roadmaps for quantum software, research, QML and hardware roles. |
How to use this hub
- New to quantum? Start with the Beginner Path and play with the Bloch Sphere.
- Know the basics? Jump into the Hands-on Labs and the Intermediate Path.
- Coming from AI/ML? Take the Quantum AI Path and the QML Classifier lab.
- Planning a career? Explore the Career Roadmaps.
Quantum computing rewards experimentation. Every lab ships with complete, runnable code — install a framework, run it, then tweak it.
A note on honesty
Quantum computing is genuinely powerful, but the field is also full of hype. Throughout this hub we try to be precise about what is proven, what is expected, and what is still open research — especially for quantum machine learning, where practical advantage is an active area of investigation.
Contributing
Quantum Resources is open source and thrives on community contributions. See the Contribution Guide to add a resource, fix a typo, or write a new lab. Good first issues are tagged on the issue tracker.
Ready? Pick a roadmap and let's compute. ⚛️