Self-Paced Quantum Portfolio Optimization in Qiskit 2.x

This is the complete recording along with slides and code files of the Quantum Portfolio Optimization Workshop.

You can learn the QAOA algorithm as applied to the portfolio optimization problem at your own pace and see its implementation on real US stock data run on real IBM quantum computer ibm_fez.

⭐ Full QAOA in 2.5 hours — theoretical foundations and Qiskit codes

⭐ Four Jupyter notebooks — Yahoo data fetching, Qiskit Primitives, QAOA on simulator for 10 stocks, and on IBM hardware for six stocks

⭐ IBM Hardware — Custom optimization routine to run on hardware in a series of single jobs through open plan

⭐ All PDF slides — complete derivations written to be a standalone reference

⭐ Full recording — Full recording available in two hours

Quantum optimization is the most commercially scrutinized corner of quantum computing, yet most engineers who want to assess it face a gap: tutorials are either toy demos with no real data or papers that assume a physics degree. This workshop closes that gap in one sitting. In 2.5 hours, you will derive QAOA from first principles, build the complete pipeline on real market data (10 and 6 US stocks, actual return and covariance figures), run it in Qiskit 2.4, and benchmark it against the exact classical optimum.

⚛️ "Do I need a paid IBM account?" No. The custom optimizer has been specifically developed to run on the free IBM Open Plan in 2 minutes.