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The book Hands-On Introduction to Quantum Computing with Python is a simple and effective initiation into the fundamentals of quantum computing. It is specifically designed for students and professionals in the tech industry with a background in computer programming. This book guides readers from the basic mathematical concepts that underpin the theoretical aspects to the design of quantum algorithms and their implementation on real quantum computers. Featuring more than 130 examples and over 100 solved programming exercises in Python, which include both basic and advanced use cases, you will gain the practical skills needed to put theory into practice. Inside, you will learn to:

• Master fundamental concepts like quantum state, quantum gate, or quantum circuit, as well as more advanced methods and highly relevant quantum algorithms (Grover, QFT, QPE, Shor, QAOA, etc.).
• Understand the core tools of quantum computing, such as superposition, entanglement, quantum parallelism, interference, or quantum teleportation.
• Formulate problems using the quantum computing paradigm and solve them using variational quantum circuits and more advanced techniques, like quantum algorithms for combinatorial optimization.
• Build and simulate quantum programs on a PC, with practical and detailed examples, using the Python programming language.

1. Mathematical foundations (sets and structures, trigonometry, vector spaces and matrices, complex numbers, probability, algorithms and their efficiency)
2. The quantum state of a qubit (bits, qubits, state vectors, Bloch sphere, density matrix, measurement operator)
3. The gates to the quantum world (abstract quantum gate model, quantum gates of one qubit, observables)
4. Parameterized quantum gates (parameterized gates, generalized rotations, parameterized circuits)
5. Multi-qubit quantum states I (computational space with multiple qubits, separability of multi-qubit quantum states, two-qubit quantum gates, controlled gates, phase kickback)
6. Multi-qubit quantum states II (theoretical model of controlled gates, multi-qubit quantum gates, SWAP test, no-cloning theorem)
7. Interpretable quantum circuits (interpretation of CNOT gates analog to classical rules, problem examples: the inverted pendulum, robotic control, quantum adder)
8. Basic tools of quantum computing (interference, entanglement, teleportation, parallelism)
9. Basic quantum algorithms (Deutsch-Jozsa, Bernstein-Vazirani, Simon, Hadamard test, Grover)
10. More quantum algorithms (QFT, QPE, quantum counting, Shor)
11. Quantum algorithms for combinatorial optimization (combinatorial optimization tools, QUBO, Ising model, the QAOA algorithm)
12. NISQ (contemporary quantum technologies, hardware and software architecture, quantum computer programming, realistic simulation)

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