Quantum Computing in Practice (IBM Learning)

IBM’s practical follow-up to the Basics of Quantum Information course, focused entirely on using real quantum hardware at scale. Where the introductory course builds mathematical foundations, this one puts you in front of actual IBM quantum processors with 100+ qubits and shows you how to get useful results out of them today.

The course covers the techniques IBM’s own researchers use when running circuits on production hardware, including the error mitigation strategies that make noisy results interpretable and the Qiskit Runtime primitives that simplify hardware access.

What you’ll learn

• Qiskit Runtime architecture: the Estimator and Sampler primitives, how they abstract hardware access, and why they are preferred over direct circuit execution for utility-scale work
• Error mitigation techniques: zero-noise extrapolation, probabilistic error cancellation, and measurement error mitigation, with worked examples showing how each technique improves hardware results
• Transpilation at scale: how Qiskit maps logical circuits to physical hardware connectivity, the cost of transpilation for large circuits, and how to control it
• Near-term application areas: quantum simulation of chemistry and materials, combinatorial optimization, and quantum machine learning, with honest assessments of where quantum advantage may emerge first
• Running utility-scale jobs: how to structure experiments, manage job queues on IBM Quantum, and handle the classical post-processing of hardware output
• Benchmarking and verification: how to assess whether your quantum results are meaningful and distinguish genuine quantum behaviour from classical noise

Course structure

The course is divided into modules covering hardware fundamentals, Qiskit Runtime, error mitigation, application areas, and best practices. Each module combines explanatory text with code examples that you can run against IBM Quantum simulators or real hardware through IBM Quantum Platform.

The course assumes familiarity with qubits, quantum gates, and basic quantum circuits. Completion of the Basics of Quantum Information course or equivalent knowledge is recommended before starting.

Who is this for?

• Developers and researchers who already understand quantum circuit basics and want to work with real IBM quantum hardware
• Quantum computing practitioners looking to scale up from toy examples to production-grade experiments
• Anyone interested in the current state of the art for near-term quantum computing
• Students transitioning from textbook quantum computing to practical hardware work

Prerequisites

Basic familiarity with qubits, quantum circuits, and Python is required. The IBM Learning course “Basics of Quantum Information” or equivalent preparation is recommended. Some familiarity with Qiskit is helpful but not strictly required, as the course introduces Qiskit Runtime from scratch.

Hands-on practice

All coding exercises use Qiskit Runtime and can target either the built-in simulators or real IBM quantum processors through a free IBM Quantum account:

• Build circuits using Qiskit and submit them through the Estimator and Sampler primitives
• Apply zero-noise extrapolation to a noisy hardware result and observe the improvement
• Transpile circuits for different IBM hardware topologies and compare the results
• Run a small variational quantum eigensolver experiment using Qiskit Runtime
• Analyse the output of a hardware job and apply measurement error mitigation

Why take this course?

Most introductory quantum computing courses stop at the simulator stage. This course starts where they leave off, teaching you how to actually use IBM’s quantum computers for real experiments. The honest treatment of noise and error mitigation is particularly valuable: it gives a realistic picture of what today’s hardware can and cannot do, which is more useful than the idealized simulator-only view that many courses provide.

The free access to IBM Quantum hardware through IBM Quantum Platform makes this course uniquely practical. You are not just learning about quantum computing in theory; you are running circuits on machines with 100+ qubits.