Machine Learning for Semiconductor Quantum Devices

Overview

Discover the revolutionary link between Machine Learning and Semiconductor Quantum Devices with this comprehensive course from Delft University of Technology, available on edX. Quantum computing represents the cutting edge of technology, with semiconductor chips playing a crucial role in the development of quantum devices.

This course tackles the major challenge in quantum computing – the rapid and efficient control of semiconductor computing chips.

Designed for students with a master's level background in physics, computer science, or electrical engineering, the course provides practical machine learning examples to enhance semiconductor quantum devices. Dive into essential techniques such as coarse and specific charge state tuning, fine tuning, and explore unsupervised quantum dot data analysis.

By the end of the course, participants will be equipped to evaluate the use of machine learning for qubit tuning and control tasks and develop a machine learning prototype ready for integration into quantum research and engineering projects.

Enhance your skills in Machine Learning, Computer Science, Supervised and Unsupervised Learning, Physics, Electrical Engineering, and Quantum Computing with this specialized offering.

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Taught by

Eliška Greplová

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Subjects