Three-stage Learning with Portable Online Hands-on Labware for Quantum-based Machine Learning Development
Quantum-based Machine Learning (QML) combines quantum computing (QC) with machine learning (ML), which can be applied in various sectors, and there is a high demand for QML professionals. However, QML is not yet in many schools' curricula. We design labware for the basic concepts of QC, ML, and QML and their applications in science and engineering fields in Google Colab, applying a three-stage learning strategy for efficient and effective student learning.
Authors
- Yong Shi (ORCID: https://orcid.org/0000-0002-3980-1425)
- Hongmei Chi (ORCID: https://orcid.org/0000-0003-4610-6479)
- Kun Suo (ORCID: https://orcid.org/0000-0001-8562-0492)
- Tu N. Nguyen (ORCID: https://orcid.org/0000-0001-7184-4102)
- Dan Lo (ORCID: https://orcid.org/0000-0003-4396-0370)
- Andrew Polisetty
Institutions
- Kennesaw State University (US)
- Florida Agricultural and Mechanical University (US)
Publication Details
- Published
- 2025-02-18
- DOI
- https://doi.org/10.1145/3641555.3705269
- Citations
- 2
- Primary Topic
- Quantum Computing Algorithms and Architecture
- Type
- article
- Field-Weighted Citation Impact
- 4.96
Funders
- National Science Foundation