Quantum
Machine
Learning
Workshop
An intensive, one-day hands-on experience introducing quantum computers for machine learning. No prior QML experience required.
In-person seats are full. Registration is open for remote (virtual) attendance only — free, and you will need your own computer.
Workshop begins in
In-person seats are full — remote registration open
"Quantum computers can solve machine learning problems that are intractable on classical hardware — and this workshop gives you the skills to run those experiments yourself."
No prior experience needed
No background in machine learning or quantum computing required — we start from the fundamentals.
Hands-on, all day
Run real experiments on quantum simulators and actual quantum hardware from your own laptop.
Expert instructors
Led by researchers from the Neural Engineering Data Consortium and Temple University faculty.
Featured Topics
QML Hardware Experiments
The capstone of the workshop — deploy your trained quantum machine learning models directly onto real quantum hardware. Experience firsthand what it means to run computations on a quantum processor, and understand the gap between simulation and real-world quantum noise.
ML Fundamentals
Classical machine learning concepts and algorithms that form the foundation for quantum enhancement.
Quantum Computing
Core principles of QC — qubits, gates, superposition, and entanglement — explained intuitively.
Linux Cluster
Basic Linux cluster computing to run large-scale QML simulation workloads efficiently.
QML Simulations
Design and run ML experiments using a quantum computing simulator before moving to hardware.
This workshop is proudly co-sponsored by the Neural Engineering Data Consortium, the Temple University Office of the Vice President for Research, and the Philadelphia section of the IEEE.
Ready to explore quantum machine learning?
Join researchers, students, and engineers for a full day of theory, simulation, and hands-on quantum hardware experiments. The in-person session is full, but you can still take part remotely.
Register — Remote AttendanceIn-person seats are full — remote registration is free and open · See full requirements →