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Quantum Physics to Quantum Computing Masterclass
New
299 students

Quantum Physics to Quantum Computing Masterclass

A beginner-friendly, step-by-step path from the basics of quantum physics to advanced quantum computing
Last updated 7/2026
English
English [Auto],

What you'll learn

  • Understand the core principles of quantum physics and quantum mechanics.
  • Explain superposition, entanglement, measurement, and uncertainty.
  • Apply vectors, matrices, complex numbers, probability, and linear algebra.
  • Understand qubits, quantum gates, Bloch spheres, and quantum circuits.
  • Compare classical computing with quantum computing.
  • Build and simulate quantum circuits using Python and Qiskit.
  • Interpret measurement results and debug quantum programs.
  • Understand Grover’s, Shor’s, Deutsch, and Deutsch-Jozsa algorithms.
  • Explore quantum teleportation, cryptography, and communication.
  • Understand quantum noise, decoherence, and error correction.
  • Compare superconducting, ion-trap, photonic, and neutral-atom hardware.
  • Complete practical quantum projects and a capstone project.

Course content

13 sections74 lectures9h 27m total length
  • What Is Quantum Physics?7:25

    Define quantum physics as the framework that predicts how matter, light, and information behave at atomic scales using amplitudes and probabilities, with a three-step mechanism: prepare, evolve, measure.

  • Classical Physics vs Quantum Physics8:04

    Compare classical physics' definite properties with quantum physics' probabilistic amplitudes, and learn how preparation, transformation, and measurement predict outcomes in real quantum systems.

  • The History of Quantum Thinking7:46
  • Why Quantum Physics Matters Today7:41

Requirements

  • No previous quantum physics experience is required.
  • No advanced mathematics background is required.
  • Basic computer skills are helpful.
  • Basic Python knowledge is useful but not mandatory.
  • A computer with an internet connection is recommended.
  • Students should be willing to learn mathematics step by step.
  • Curiosity about physics, computing, or emerging technology is encouraged.
  • All major concepts are introduced from a beginner-friendly level.
  • Access to Python, Jupyter Notebook, or Google Colab is helpful.
  • Qiskit installation guidance is included in the course.

Description

This course contains the use of artificial intelligence.

Step into the fascinating world of quantum physics and learn how its revolutionary principles power the next generation of quantum computers. Quantum Physics to Quantum Computing Mastery is a beginner-friendly, step-by-step course designed to take you from the fundamentals of quantum mechanics to advanced quantum computing concepts, algorithms, hardware, and practical projects.

You do not need a background in physics or advanced mathematics to begin. The course introduces essential topics using clear explanations, visual intuition, practical examples, and hands-on programming exercises. You will first explore the foundations of quantum physics, including wave-particle duality, superposition, measurement, the uncertainty principle, quantum states, and entanglement.

Next, you will build the mathematical foundation required for quantum computing. You will learn algebra, vectors, matrices, complex numbers, probability, statistics, and linear algebra in an approachable way. These concepts will help you understand how qubits, quantum gates, state vectors, and quantum circuits work.

The course then introduces the fundamentals of quantum information science, including bits versus qubits, the Bloch sphere, single-qubit operations, multi-qubit systems, quantum gates, and circuit design. You will discover how quantum computers differ from classical computers and explore important applications in cryptography, optimization, scientific simulation, artificial intelligence, and machine learning.

Using Python for quantum computing and Qiskit, you will create quantum circuits, run simulations, interpret measurement results, and debug quantum programs. You will also study popular quantum algorithms, including the Deutsch algorithm, Deutsch-Jozsa algorithm, Grover’s search algorithm, and Shor’s algorithm. The course explains quantum speedup and helps you understand when quantum algorithms can provide meaningful advantages.

As you progress, you will explore intermediate and advanced topics such as tensor products, Bell states, quantum teleportation, quantum cryptography, variational quantum algorithms, the Quantum Approximate Optimization Algorithm, quantum machine learning, noise models, and quantum error mitigation.

You will also gain a practical understanding of quantum error correction, decoherence, logical qubits, physical qubits, fault-tolerant quantum computing, and the challenges involved in scaling quantum systems.

The hardware section examines leading quantum technologies, including superconducting qubits, ion traps, photonic quantum computing, and neutral-atom systems. You will compare their strengths, limitations, and potential roles in the future of quantum technology.

Hands-on quantum computing projects include building a quantum random number generator, creating Bell states, implementing Grover’s algorithm, simulating quantum circuits, and exploring quantum encryption. You will complete a capstone project that demonstrates your growing quantum computing skills.

By the end of the course, you will have a strong foundation in quantum mechanics, quantum programming, Qiskit, quantum algorithms, quantum hardware, and quantum information science. You will also learn about quantum computing careers, research pathways, portfolio development, interview preparation, and opportunities for continued learning.

Whether you are a student, developer, engineer, researcher, technology professional, or curious beginner, this course provides a structured path toward mastering one of the most exciting and transformative technologies of the future.

Who this course is for:

  • Beginners who want to understand quantum physics and quantum computing.
  • Students exploring careers in quantum technology or scientific computing.
  • Python developers interested in quantum programming and Qiskit.
  • Software engineers preparing for the future of computing.
  • Data scientists and AI professionals exploring quantum machine learning.
  • Physics and mathematics students seeking practical computing skills.
  • Researchers interested in quantum algorithms and hardware.
  • Technology professionals evaluating quantum computing applications.
  • Educators looking for a structured introduction to quantum concepts.
  • Curious learners who want a step-by-step path into quantum technology.