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future Advanced 21 lessons

Quantum Computing Intro

Program the next era of computing. Master Qubits, Superposition, and Entanglement using Python and Qiskit on real IBM Quantum hardware.

Quantum computing uses the laws of quantum mechanics to solve problems classical computers cannot. This course introduces the physics and logic behind quantum algorithms. You will learn to manipulate Qubits using gates (Hadamard, CNOT), visualize states on the Bloch Sphere, and write circuits using IBM's Qiskit SDK. We execute code on real cloud-based quantum processors to run Grover's Search algorithm and understand the potential of quantum speedup.

✅ 100% Free & Lifetime Access
⏱️ 5-Minute Lessons (Bite-sized learning)
🚀 21-Lesson Path (Independent modules)
📱 Mobile Friendly (Learn anywhere)
Physicists
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Secure Enrollment via SSL

Complete Course Syllabus

  • 1
    The Qubit
    Superposition, measurement, and probabilistic states.
  • 2
    Quantum Gates
    Manipulating qubits with X, Y, Z, and H gates.
  • 3
    Entanglement
    Linking particles for correlated states (Spooky Action).
  • 4
    Qiskit Basics
    Writing your first circuit in Python code.
  • 5
    Real Hardware
    Queuing jobs on the IBM Quantum cloud.

Estimated completion time: 21 lessons • Self-paced learning • Lifetime access

Career Outlook

Estimated Salary
$120k - $180k

Career Paths

Quantum Software Eng $130k-$190k
Research Scientist $140k-$200k
HPC Engineer $120k-$170k

What You Will Learn

Write quantum programs using Python and Qiskit SDK
Construct quantum circuits using Hadamard and CNOT gates
Execute experiments on real IBM Quantum cloud hardware
Visualize quantum states using the Bloch Sphere
Implement basic algorithms like Grover's Search

Skills You Will Gain

Quantum Physics Qiskit Python Linear Algebra Circuit Design

Who Is This For

Computer Scientists
Physics Grads
Research Engineers

Prerequisites

Python
Linear Algebra

Quantum Computing Intro FAQs

Real hardware?

Yes, we access IBM's cloud quantum processors.

Physics degree?

Helpful, but we focus on the logic/code layer.

Is it useful yet?

Mostly for research and optimization POCs today.

Math?

Complex numbers and matrix multiplication needed.

Need more info?
All Reork courses are 100% free, self-paced, and fully accessible on mobile devices. No prior experience is required. Read our full Platform FAQ.

Tech Stack & Tools

IBM Quantum Lab
Qiskit
Jupyter Notebook
Python

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