This course provides a hands-on, programming-heavy introduction to quantum computing applications with IBM Qiskit. Students learn core quantum concepts (qubits, superposition, entanglement and measurement), quantum circuit building and quantum machine learning (QML) techniques, including variational quantum classifiers (VQC), quantum support vector machines (QSVM) and quantum neural networks (QNNs).
Emphasis is on practical skills, with weekly team Technique Labs that include pair-programming, version control and short milestone submissions. A single team project applies QML to a small biology/chemistry dataset and compares quantum results with classical baselines. The course uses IBM simulators and introduces managed access to real quantum devices. Credits: 4