Quantum Hub Curriculum*

*Subject to change based on academic and user feedback through 2025.

THE QUANTUM HUB USER JOURNEY

How the Ingenii Quantum Hub takes you from quantum fundamentals through developing your own novel QML algorithms.

Beta Release

In the first release of the Quantum Hub, users will acquire the basics of quantum computing concepts, including: 

  • Understand the difference between classical bits and quantum bits. 

  • Learn to visually manipulate quantum gates such as bit flips (represented by crossing paths) and phase flips (indicated by color changes). 

  • Comprehend the principles of quantum superposition and entanglement, alongside the probabilistic essence of quantum computing. 

  • Explore complex quantum gates and universal quantum sets. 

  • Learn how to leverage the Quantum Hub for addressing real-world applications. 

Chapter 1: Introduction  

​Chapter 2: Bit and phase flips  

​Chapter 3: Superposition  

​Chapter 4: Quantum entanglement  

​Chapter 5: Universality  

Chapter 6: Quantum Chemistry*  

Chapter 7: Quantum Bayesian networks*

*Either Chapter 6 or 7 will be present in the 2024 release 

Full Release

In the full release, users will delve into quantum algorithms, for both Noisy Intermediate Scale Quantum (NISQ) and fault-tolerant computers: 

  • Understand how to measure probabilities and observables in quantum circuits. 

  • Understand the quantum SWAP gate to test state similarities. 

  • Learn to create highly entangled states such as Bell, GZH and W states. 

  • Learn to design search algorithms using quantum computing. 

  • Learn to diagonalize and solve systems of equations with quantum advantage. 

  • Explore data encoding methods and their applications to quantum machine learning. 

  • Learn to design variational circuits for machine learning and optimization tasks.  

​​Chapter 8: Measurements  

Chapter 9: Quantum SWAP  

​Chapter 10: Non-locality  

​Chapter 11: Quantum search algorithms  

Chapter 12: Quantum phase estimation  

​Chapter 13: Solving systems of equations  

​Chapter 14: Data encoding methods  

​Chapter 15: Kernel methods  

​Chapter 16: Variational quantum circuits 

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