Learn QISKIT with Real Code Examples

Quantum algorithm consulting

Education and training in quantum computing

Hybrid classical-quantum optimization solutions

Develop quantum machine learning pipelines

Research collaboration and publications

Support for more quantum hardware backends

Enhanced noise mitigation techniques

Improved quantum machine learning modules

Better integration with classical optimization frameworks

Expanded educational tutorials and community contributions

If targeting non-IBM hardware exclusively

For purely classical computation problems

When high-fidelity quantum results are required but only noisy devices are available

If Python-based workflow is not desired

For extremely large qubit circuits beyond classical simulation capability

Qiskit is a Python framework for quantum computing, offering both simulation and access to real IBM Quantum devices.

Supports quantum circuit design, execution, and analysis.

Includes specialized libraries for chemistry, optimization, and machine learning.

Rich visualization and simulation tools help develop and debug algorithms.

Widely adopted in research, industry, and educational programs.

Is Qiskit free?

Yes - open-source under Apache 2.0 license.

Which quantum devices does Qiskit support?

IBM Quantum devices and simulators.

Can Qiskit simulate quantum algorithms?

Yes - via Aer simulator or other classical simulators.

Does Qiskit support quantum chemistry?

Yes - via Qiskit Nature module.

Can Qiskit be used for optimization problems?

Yes - via Qiskit Optimization library.