In this series of tutorials, we provide a basic introduction into some of the fundamental concepts behind supervised quantum machine learning algorithms.


  • Knowledge of basic notions of quantum computing is assumed.
  • We provide the programming examples in qiskit.
  • So if both things are known to you, you can directly start out. Otherwise, the introductory chapters of the qiskit textbook might be a great starting point.
  • Knowledge of classical supervised learning is not really necessary, but certainly helpful. The Coursera course by is awesome.

If you would like to have further information, please contact us.

An interview on the state of QML with Manuel Rudolph

To finish the serious we interviewed Manuel Rudolph, who worked on QML for several years now and discussed with him the state-of-the-art. The goal is to bring to you an independent point-of-view that allows all of our visitors to form a more educated opinion. Read the interview

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