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Uppsala University
Quantum Machine Learning
The course introduces Quantum Machine Learning (QML) and explores how quantum computing can be combined with classical machine learning methods to solve problems in physics and engineering. You gain hands-on experience developing and training quantum and hybrid models using tools such as Qiskit, PennyLane, and class…
- Higher education
- Information unavailable
- 22 March 2027
- Uppsala
- Information unavailable
- 33 %
Overview
The course introduces Quantum Machine Learning (QML) and explores how quantum computing can be combined with classical machine learning methods to solve problems in physics and engineering. You gain hands-on experience developing and training quantum and hybrid models using tools such as Qiskit, PennyLane, and classical ML libraries, and running them on simulators and real quantum hardware. The course covers topics including variational quantum circuits, quantum neural networks, quantum kernel methods, QAOA, VQE, and quantum annealing, and culminates in a practical QML project.
Admission scores
Entry requirements
120 credits in science/engineering. In addition, one of the following alternatives: 1) Quantum Physics or Quantum Physics F. Programming Technology I or Introduction to Computational Science. Linear Algebra II. 2) Introduction to Quantum Computers and Quantum Programming. Proficiency in English equivalent to the Swedish upper secondary course English 6.
The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.
Source, measure and data quality
- Source
- Skolverket Susa-navet
- Period
- 2027-03-22
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.uu.1fa020.63007.20271
- Last checked
- 2026-09-23T10:39:41.205927+00:00
- Limitation
- Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.
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- Programme or course starts
- Programme or course ends
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About the provider
Sources and data quality
Education facts for the selected offering come from Skolverket Susa-navet.
Retrieved . Published . Times are shown in Swedish local time.
Source identity and publication version
- Publication version
- 8e217193-f5fa-4778-b085-a4521fd03e8d
- Education identity in the source
- i.uoh.uu.1fa020.63007.20271
- Offering identity in the source
- e.uoh.uu.1fa020.63007.20271
- Education-form source code
- HS
- Education code in the source
- 1FA020
- Change time according to the source
- 2026-09-08T12:32:12
The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.