Course Outline


Overview of Quantum Physics Theories Applied in Quantum Computing

  • Fundamentals of quantum superposition
  • Fundamentals of quantum entanglement
  • Mathematical foundations of quantum computing

Overview of Quantum Computing

  • Differentiating quantum computing and classical electronic computing
  • Integrating quantum behaviors into quantum computing
  • The Qubit
  • Implementing the Dirac notation
  • Computational basis measurements in quantum computing
  • Quantum circuits and quantum oracles

Working with Vectors and Matrices in Quantum Computing

  • Matrix multiplication using quantum physics
  • Conventions of tensor products

Applying Advanced Matrix Concepts to Quantum Computing

Overview of Quantum Computers and Quantum Simulators

  • The quantum hardware and its components
  • Running a quantum simulator
  • Executable quantum mechanisms in a quantum simulation
  • Performing quantum computations in a quantum computer

Working with Quantum Computing Models

  • Logic and functions of different quantum gates
  • Understanding superposition and entanglement effects on quantum gates

Utilizing Shor's Algorithm and  Quantum Computing Cryptography

Implementing Grover's Algorithm in Quantum Computing

Estimating a Quantum Phase in a Quantum Computer

  • The quantum Fourier transform

Writing Basic Quantum Computing Algorithms and Programs for a Quantum Computer

  • Utilizing the right tools and language for quantum computing
  • Setting up quantum circuits and specifying quantum gates

Compiling and Running Quantum Algorithms and Programs in a Quantum Computer

Testing and Debugging Quantum Algorithms and Quantum Computer Programs

Identifying and Correcting Algorithm Errors Using Quantum Error Correction (QEC)

Overview of Quantum Computing Hardware and Architecture

Integrating Quantum Algorithms and Programs with the Quantum Hardware


Advancing Quantum Computing for Future Quantum Information Science Applications

Summary and Conclusion


  • Knowledge of mathematical methods in probability and linear algebra
  • Comprehension of foundational computer science theories and algorithms
  • An understanding of elementary quantum physics concepts
  • Basic experience with quantum mechanics models and theories


  • Computer Scientists
  • Engineers
 21 Hours

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