Certificate in Quantum Computing: Foundations, Programming, and Applications
Course provided by Model Institute of Engineering & Technology
11 modules
Master quantum computing while exploring cutting-edge applications.
6 Level NCrF
National Credit Framework
300 Hours
Flexible Learning
Beginner Level
No prior experience required
Certificate Course
09 Credit
Course Overview
This course introduces quantum computing fundamentals, including quantum mechanics, mathematical modeling, and circuit design using Qiskit. Participants gain hands-on experience with quantum algorithms and Python programming, while exploring emerging paradigms such as neuromorphic and optical computing. The capstone project simulates real-world quantum solutions in areas like optimization, encryption, and scientific computing.
Key Learning Highlights
Hands-on quantum circuit design with Qiskit
Foundational Python programming for quantum computing
Exposure to quantum algorithms and real-world applications
Introduction to emerging paradigms: neuromorphic & optical computing
Capstone project simulating practical quantum solutions
Tools & Platforms Used
Learning Outcome
By the end of this course, students will be able to:
Comprehend the principles of quantum mechanics relevant to quantum computing.
Apply linear algebra, matrices, and probability theory to quantum systems.
Build and simulate quantum programs using Qiskit and Python.
Implement and analyze core quantum algorithms such as Grover’s and Shor’s.
Apply quantum computing to real-world problems in optimization, cryptography, and simulation.
Master the course with just 11 Modules
Learn quantum computing fundamentals, program quantum circuits with Qiskit, explore emerging paradigms, and solve real-world problems with a hands-on capstone.
Module 1
Foundations of Quantum Mechanics – Wave-particle duality, quantum states, Schrödinger & Heisenberg pictures, observables, expectation values, fermions/bosons.
Module 2
Mathematics for Quantum Computing – Complex numbers, matrices, linear algebra, tensor products, superposition, entanglement, Bracket notation, multi-qubit systems
Module 3
Python for Quantum Computing – Python basics, object-oriented programming, NumPy, Jupyter Notebooks for quantum simulation.
Module 4
Qiskit Essentials – Qiskit SDK, IBM Quantum Composer, building basic circuits, simulation vs execution on quantum hardware.
Module 5
Quantum Gates & Circuits – Single-qubit and multi-qubit gates, measurement, Bloch sphere visualization, circuit optimization.
Module 6
Grover’s Algorithm – Oracle design, amplitude amplification, search optimization, Qiskit implementation.
Module 7
Shor’s Algorithm – Quantum Fourier transform, modular exponentiation, factoring demonstration in Qiskit.
Module 8
Other Quantum Algorithms – Deutsch-Jozsa, Variational Quantum Eigensolver (VQE), Quantum Approximate Optimization Algorithm (QAOA).
Module 9
Quantum Error Correction & Noise – Decoherence, error detection, surface codes, mitigation techniques in Qiskit.
Module 10
Quantum Applications – Cryptography, drug discovery, optimization, machine learning, simulation.
Module 11
Industry Exposure
Module 10
Industry Exposure
Module 11
Design and simulation of a quantum algorithm or application; integration with IBM Quantum hardware.
Roles
Quantum Programmer / Emerging Tech Analyst
