Quantum Computing
Quantum Basic
An introduction to quantum principles, circuit design, and practical workflows using Qiskit.
Curriculum
Course Modules
Each module includes guided lectures and practical lab sessions.
Module 1
Module 1: Linear Algebra & Qubits
Module 1
Module 1: Linear Algebra & Qubits
Lectures
- Lecture 1.1 - Complex Numbers and Vector Spaces
- Lecture 1.2 - Dirac Notation and State Representation
- Lecture 1.3 - Tensor Products and Multi-Qubit Systems
- Lecture 1.4 - Introduction to Qubits and Bloch Sphere
Labs
- Lab 1 - Representing Qubits with Python (NumPy)
Module 2
Module 2: Quantum Circuits & Gates
Module 2
Module 2: Quantum Circuits & Gates
Lectures
- Lecture 2.1 - Classical vs Quantum Circuits
- Lecture 2.2 - Single-Qubit Gates (X, Y, Z, H)
- Lecture 2.3 - Multi-Qubit Gates (CNOT, SWAP)
- Lecture 2.4 - Universal Gate Sets
Labs
- Lab 2 - Building Basic Circuits using Qiskit
Module 3
Module 3: Quantum Measurement & States
Module 3
Module 3: Quantum Measurement & States
Lectures
- Lecture 3.1 - Measurement Postulate
- Lecture 3.2 - Probability Amplitudes
- Lecture 3.3 - Mixed States and Density Matrices
- Lecture 3.4 - State Visualization
Labs
- Lab 3 - Simulating Measurements and Statevectors
Module 4
Module 4: Quantum Entanglement
Module 4
Module 4: Quantum Entanglement
Lectures
- Lecture 4.1 - Entanglement Basics
- Lecture 4.2 - Bell States
- Lecture 4.3 - EPR Paradox and Non-locality
Labs
- Lab 4 - Creating Entangled Circuits
Module 5
Module 5: Fundamental Quantum Algorithms
Module 5
Module 5: Fundamental Quantum Algorithms
Lectures
- Lecture 5.1 - Deutsch Algorithm
- Lecture 5.2 - Deutsch-Jozsa Algorithm
- Lecture 5.3 - Bernstein-Vazirani Algorithm
- Lecture 5.4 - Simon's Algorithm
Labs
- Lab 5 - Implementing Basic Algorithms
Module 6
Module 6: Advanced Quantum Algorithms
Module 6
Module 6: Advanced Quantum Algorithms
Lectures
- Lecture 6.1 - Grover's Search Algorithm
- Lecture 6.2 - Quantum Fourier Transform (QFT)
- Lecture 6.3 - Phase Estimation Algorithm
- Lecture 6.4 - Shor's Algorithm
Labs
- Lab 6 - Grover Search Implementation
Module 7
Module 7: Noise & Quantum Error Correction
Module 7
Module 7: Noise & Quantum Error Correction
Lectures
- Lecture 7.1 - Noise in Quantum Systems
- Lecture 7.2 - Decoherence
- Lecture 7.3 - Quantum Error Correction Codes
- Lecture 7.4 - Fault-Tolerant Quantum Computing
Labs
- Lab 7 - Simulating Noise Models
Module 8
Module 8: Quantum Hardware
Module 8
Module 8: Quantum Hardware
Lectures
- Lecture 8.1 - Quantum Hardware Overview
- Lecture 8.2 - Superconducting Qubits
- Lecture 8.3 - Ion Trap Systems
- Lecture 8.4 - NISQ Devices
Labs
- Lab 8 - Running Circuits on IBM Quantum Experience
Module 9
Module 9: Variational Quantum Algorithms
Module 9
Module 9: Variational Quantum Algorithms
Lectures
- Lecture 9.1 - Variational Circuits
- Lecture 9.2 - VQE (Variational Quantum Eigensolver)
- Lecture 9.3 - QAOA (Quantum Approximate Optimization Algorithm)
Labs
- Lab 9 - Implementing VQE