Most quantum computing material is written for one of two readers: the physicist who already knows the math, or the newcomer who gets an analogy and never the math behind it. If you are a developer or an ML engineer who wants to work on real projects, neither one gets you there.

EigenOrbit Academy is a video course on quantum information processing, from a single qubit to your first running algorithm.

How a lecture is built

Each lecture is 3 to 5 minutes long. Every concept follows the same order:

  1. an analogy,
  2. the math,
  3. where the analogy breaks down.

The third step is the one most courses skip, and it is where most misconceptions about quantum computing come from. After each lecture there are questions on what was just covered.

The lectures are written and recorded by our own quantum specialists.

What the program covers

The program has 12 modules. The first two:

Module Lectures Length Topics
1. Why quantum computing 3 ~13 min Why organizations invest, what current hardware can and cannot do, which problems are worth trying
2. Quantum computing foundations 7 ~31 min Qubits, superposition, entanglement, measurement, gates

The modules that follow cover:

  • classical ML foundations, as preparation for the quantum versions;
  • the software and hardware stack, including superconducting and trapped-ion qubits;
  • core algorithms: Grover, QAOA, VQE, QSVM, HQNN, HHL;
  • hybrid quantum-classical computing, with use cases in finance, energy, manufacturing, healthcare and materials science;
  • a hands-on module and an end-to-end walkthrough.

The full program is published on the page, so you can see what is in it before you start.

Every quantum method next to a classical baseline

Each quantum method in the course is compared against a classical baseline. The course says where quantum ML has been shown to work and where it has not.

For ML readers, the course connects backpropagation to variational circuits, so QSVM, HQNN, VQE and QAOA build on what you already know.

The hands-on module

In the hands-on module you describe your own problem. You get back a hybrid solution, benchmarked against a classical baseline, as code and a report.

Quizzes and certificate

Every module ends with a graded quiz. After passing them you get a PDF certificate that records lectures completed, quiz accuracy and study time. It has a unique ID and a QR code for verification, and can be added to LinkedIn.

Who it is for

  • New to quantum. No physics background needed.
  • CS and ML students. The algorithms used in quantum ML, with their limits stated.
  • Self-learners preparing for real projects. The same terms and algorithms used in practice, and a final module that goes through the full workflow.
  • Researchers and instructors. Source-checked explanations and reusable teaching material.

Access

€99, one-time payment. This includes all current and future modules, quizzes, certificates and worked examples.

Links

Follow EigenOrbit to see new modules as they are added.