Specialization - 12 course series
Introduction to Quantum Computing
Establishes foundational understanding of quantum computing, classical vs quantum systems, and real-world applications.
Tools / Technologies: IBM Quantum Experience, Google Colab
Assignments : Write a brief on quantum vs classical computing; explore quantum
Linear Algebra for Quantum Computing
Covers vectors, matrices, complex numbers, and transformations used in quantum systems.
Tools / Technologies : Python (NumPy)
Assignments : Solve linear algebra problems relevant to quantum states
Quantum Mechanics Basics
Introduces core principles like superposition, entanglement, and measurement.
Tools / Technologies : Conceptual tools, simulations
Assignments : Explain quantum concepts with examples
Qubits & Quantum Gates
Covers qubits, Bloch sphere, and basic quantum gates (X, Y, Z, H).
Tools / Technologies : Qiskit
Assignments : Implement basic quantum circuits
Quantum Circuits & Measurement
Focuses on building quantum circuits and understanding measurement outcomes.
Tools : Qiskit
Outcome: Build and simulate quantum circuits
Quantum Algorithms (Part 1)
Introduces professional toolchains for scalable development. Students move beyond Remix to frameworks like Hardhat & Truffle.
Tools : Qiskit
Outcome: Implement simple quantum algorithms
Quantum Algorithms (Part 2)
Covers advanced algorithms like Shor’s algorithm and amplitude amplification.
Tools : Qiskit
Outcome : Simulate advanced algorithms (conceptual level)
Quantum Programming
Teaches writing quantum programs and running them on simulators and real hardware.
Tools : Qiskit, IBM Quantum Lab
Outcome : Execute quantum programs on cloud quantum systems
Quantum Error Correction
Introduces noise, decoherence, and basic error correction techniques.
Tools : - Qiskit (noise models)
Outcome: Simulate noise and error mitigation
Quantum Applications
Explores applications in cryptography, optimization, and machine learning.
Tools : Qiskit, research tools
Outcome : Analyze real-world use cases
Quantum Hardware & Ecosystem
Covers quantum hardware types, current limitations, and ecosystem overview
Tools : IBM Quantum Docs
Outcome : Build and present quantum computing project
Capstone Project & Career Development
End-to-end quantum project and portfolio building.
Tools : - All tools integrated; Twitter, GitHub, Devpost
Outcome: Build & deploy also Present project; submit GitHub repo & report.
Quantum Computing
Curriculum
LEVEL:
Beginner to Intermediate
FOCUS :
Core IT, Cloud Fundamentals, and Hands-on Cloud Deployment Skills
GOAL:
Prepare learners for foundational cloud roles and certifications (AWS CCP, AZ-900, GCP Digital Leader)
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