vinod sharma .in Solution Architect, Author & Educator
Courses, books, roadmaps, and tutorials to help developers build real-world skills.
© 2026 Vinod Sharma. All rights reserved.
Quantum Computing & Engineering A rigorous roadmap for learning quantum computing from the ground up. This path covers the mathematical prerequisites, quantum mechanics, qubit operations, quantum programming, key algorithms, error correction, quantum ML, simulation, networking, hardware, hybrid systems, and real-world applications.
12 milestones in this roadmap
Step 1 beginner 6-8 weeks
Linear Algebra & Complex Numbers Build the mathematical foundation for quantum computing with complex numbers, vector spaces, tensor products, and Dirac notation.
1 Complex numbers: Euler formula, polar form, conjugates, and modulus 2 Vector spaces, inner products, and orthonormal bases 3 Matrix operations: unitary, Hermitian, and projector matrices 4 Eigenvalues, eigenvectors, and spectral decomposition 5 Tensor products and multi-qubit state spaces 6 Dirac bra-ket notation for quantum states and operators
Python / NumPy for matrix computation MATLAB / Mathematica Qiskit Textbook (online) 3Blue1Brown linear algebra series
Step 1 beginner 6-8 weeks
Linear Algebra & Complex Numbers Build the mathematical foundation for quantum computing with complex numbers, vector spaces, tensor products, and Dirac notation.
1 Complex numbers: Euler formula, polar form, conjugates, and modulus 2 Vector spaces, inner products, and orthonormal bases 3 Matrix operations: unitary, Hermitian, and projector matrices 4 Eigenvalues, eigenvectors, and spectral decomposition 5 Tensor products and multi-qubit state spaces
Step 2 beginner 6-8 weeks
Quantum Mechanics Fundamentals Study the core quantum mechanics principles that directly govern quantum computation: superposition, entanglement, and measurement.
1 Superposition principle and probability amplitudes 2 Quantum entanglement, Bell states, and non-locality 3 Measurement postulate, Born rule, and wave function collapse 4 No-cloning theorem and its implications for quantum computing
Step 3 beginner 4-6 weeks
Qubits, Gates & Circuits Learn the building blocks of quantum circuits including qubit representations, single- and multi-qubit gates, and universal gate sets.
1 Qubit state representation on the Bloch sphere 2 Single-qubit gates: Hadamard, Pauli X/Y/Z, phase (S), T-gate, and rotations 3 Multi-qubit gates: CNOT, Toffoli (CCX), SWAP, and controlled-U 4 Universal gate sets and gate decomposition
Step 4 intermediate 6-8 weeks
Quantum Programming (Qiskit & Cirq) Write quantum programs using Qiskit and Cirq, simulate circuits classically, and run experiments on real quantum hardware.
1 Qiskit Terra: circuit construction, transpilation, and backend selection 2 Qiskit Aer: statevector, QASM, and density matrix simulators 3 Cirq: moments, devices, noise models, and custom gates 4 Running on real hardware: IBM Quantum, job queuing, and shot-based measurement
Step 5 intermediate 8-10 weeks
Quantum Algorithms (Shor's & Grover's) Master the landmark quantum algorithms that demonstrate exponential and quadratic speedups over classical computation.
1 Deutsch-Jozsa and Bernstein-Vazirani as introductory oracle algorithms 2 Quantum Fourier Transform and its role in period-finding 3 Shor's factoring algorithm: quantum period-finding and modular exponentiation 4 Grover's search algorithm: amplitude amplification and oracle construction
Step 6 advanced 6-8 weeks
Quantum Error Correction Understand why quantum error correction is essential and study the codes that enable fault-tolerant quantum computation.
1 Types of quantum errors: bit-flip, phase-flip, and combined errors 2 Three-qubit repetition code and the Shor 9-qubit code 3 CSS codes, Steane code, and stabiliser formalism 4 Surface codes: lattice surgery, thresholds, and logical operations 5
Step 7 advanced 6-8 weeks
Quantum Machine Learning Explore quantum-classical hybrid ML algorithms including variational circuits, quantum kernels, and quantum neural networks.
1 Variational Quantum Eigensolver (VQE): ansatz design and classical optimisers 2 QAOA for combinatorial optimisation problems 3 Parameterised quantum circuits and barren plateau problem 4 Quantum kernel methods for classification and regression 5
Step 8 advanced 6-8 weeks
Quantum Simulation Learn how quantum computers simulate quantum systems intractable for classical machines, with applications in chemistry and materials science.
1 Hamiltonian simulation and Trotterisation 2 Molecular ground-state energy calculation with VQE 3 Quantum dynamics simulation for chemical reactions 4 Materials science applications: strongly correlated electron systems 5
Step 9 advanced 4-6 weeks
Quantum Networking Study quantum communication protocols including QKD, teleportation, and the foundations of a future quantum internet.
1 Quantum key distribution: BB84, E91, and decoy-state protocols 2 Quantum teleportation and entanglement swapping 3 Quantum repeaters, entanglement distillation, and purification 4 Quantum memory requirements and coherence time challenges 5
Step 10 advanced 4-6 weeks
Quantum Hardware Understanding Develop a working understanding of quantum hardware platforms, their trade-offs, and the engineering challenges of building quantum processors.
1 Superconducting qubits: transmon design, dilution refrigerators, and microwave control 2 Trapped ion qubits: Paul traps, laser-driven gates, and ion shuttling 3 Photonic quantum computing: linear optics, squeezed states, and boson sampling 4 Neutral atom arrays: optical tweezers, Rydberg interactions, and reconfigurability
Step 11 advanced 4-6 weeks
Hybrid Classical-Quantum Systems Design practical hybrid quantum-classical applications that leverage both paradigms for near-term quantum advantage.
1 Variational algorithms: classical optimiser + quantum circuit feedback loops 2 Problem decomposition: identifying quantum-suitable sub-problems 3 Classical pre- and post-processing for quantum algorithm output 4 Error mitigation techniques for NISQ-era hybrid workflows
Step 12 advanced 3-4 weeks
Quantum Applications in Industry Explore real-world quantum computing applications in finance, pharma, logistics, and cybersecurity and understand where quantum advantage is nearest.
1 Finance: portfolio optimisation, Monte Carlo pricing, and risk analysis 2 Pharma: molecular simulation for drug discovery and protein folding 3 Logistics: vehicle routing, supply chain, and scheduling optimisation 4 Cybersecurity: quantum-safe cryptography transition and random number generation Ready to start this journey? Browse our courses and books to begin your learning path.
6 Dirac bra-ket notation for quantum states and operators
Python / NumPy for matrix computation MATLAB / Mathematica Qiskit Textbook (online) 3Blue1Brown linear algebra series
5
Uncertainty principle and complementarity
6 Density matrices, mixed states, and decoherence
Feynman Lectures on Physics (Vol. III) MIT OCW 8.04 / 8.05 materials QuTiP (Python quantum simulation) Quantum Mechanics textbook (Griffiths or Sakurai)
Step 2 beginner 6-8 weeks
Quantum Mechanics Fundamentals Study the core quantum mechanics principles that directly govern quantum computation: superposition, entanglement, and measurement.
1 Superposition principle and probability amplitudes 2 Quantum entanglement, Bell states, and non-locality 3 Measurement postulate, Born rule, and wave function collapse 4 No-cloning theorem and its implications for quantum computing 5 Uncertainty principle and complementarity 6 Density matrices, mixed states, and decoherence
Feynman Lectures on Physics (Vol. III) MIT OCW 8.04 / 8.05 materials QuTiP (Python quantum simulation) Quantum Mechanics textbook (Griffiths or Sakurai)
5
Quantum circuit diagrams: reading, writing, and circuit depth/width
6 Entanglement generation with Bell circuits and GHZ states
Qiskit Cirq Quirk (online circuit simulator) IBM Quantum Composer
Step 3 beginner 4-6 weeks
Qubits, Gates & Circuits Learn the building blocks of quantum circuits including qubit representations, single- and multi-qubit gates, and universal gate sets.
1 Qubit state representation on the Bloch sphere 2 Single-qubit gates: Hadamard, Pauli X/Y/Z, phase (S), T-gate, and rotations 3 Multi-qubit gates: CNOT, Toffoli (CCX), SWAP, and controlled-U 4 Universal gate sets and gate decomposition 5 Quantum circuit diagrams: reading, writing, and circuit depth/width 6 Entanglement generation with Bell circuits and GHZ states
Qiskit Cirq Quirk (online circuit simulator) IBM Quantum Composer
5
Noise models: depolarising, amplitude damping, and readout error
6 Mitigation techniques: measurement error mitigation and zero-noise extrapolation
IBM Qiskit Google Cirq IBM Quantum Platform Amazon Braket
Step 4 intermediate 6-8 weeks
Quantum Programming (Qiskit & Cirq) Write quantum programs using Qiskit and Cirq, simulate circuits classically, and run experiments on real quantum hardware.
1 Qiskit Terra: circuit construction, transpilation, and backend selection 2 Qiskit Aer: statevector, QASM, and density matrix simulators 3 Cirq: moments, devices, noise models, and custom gates 4 Running on real hardware: IBM Quantum, job queuing, and shot-based measurement 5 Noise models: depolarising, amplitude damping, and readout error 6 Mitigation techniques: measurement error mitigation and zero-noise extrapolation
IBM Qiskit Google Cirq IBM Quantum Platform Amazon Braket
5
Quantum phase estimation and its applications
6 Quantum walk algorithms and the HHL algorithm for linear systems
Qiskit Algorithms module Cirq Classiq (high-level quantum programming) Quirk for algorithm visualisation
Step 5 intermediate 8-10 weeks
Quantum Algorithms (Shor's & Grover's) Master the landmark quantum algorithms that demonstrate exponential and quadratic speedups over classical computation.
1 Deutsch-Jozsa and Bernstein-Vazirani as introductory oracle algorithms 2 Quantum Fourier Transform and its role in period-finding 3 Shor's factoring algorithm: quantum period-finding and modular exponentiation 4 Grover's search algorithm: amplitude amplification and oracle construction 5 Quantum phase estimation and its applications 6 Quantum walk algorithms and the HHL algorithm for linear systems
Qiskit Algorithms module Cirq Classiq (high-level quantum programming) Quirk for algorithm visualisation
Fault-tolerant gates and the threshold theorem
6 Logical qubits, code distance, and the overhead of error correction
Qiskit Ignis / Qiskit QEC Stim (Google, fast stabiliser simulation) PyMatching (MWPM decoder) IBM Quantum for NISQ experiments
Step 6 advanced 6-8 weeks
Quantum Error Correction Understand why quantum error correction is essential and study the codes that enable fault-tolerant quantum computation.
1 Types of quantum errors: bit-flip, phase-flip, and combined errors 2 Three-qubit repetition code and the Shor 9-qubit code 3 CSS codes, Steane code, and stabiliser formalism 4 Surface codes: lattice surgery, thresholds, and logical operations 5 Fault-tolerant gates and the threshold theorem 6 Logical qubits, code distance, and the overhead of error correction
Qiskit Ignis / Qiskit QEC Stim (Google, fast stabiliser simulation) PyMatching (MWPM decoder) IBM Quantum for NISQ experiments
Quantum neural networks and expressibility
6 Benchmarking quantum advantage claims in ML applications
PennyLane Qiskit Machine Learning TensorFlow Quantum Amazon Braket
Step 7 advanced 6-8 weeks
Quantum Machine Learning Explore quantum-classical hybrid ML algorithms including variational circuits, quantum kernels, and quantum neural networks.
1 Variational Quantum Eigensolver (VQE): ansatz design and classical optimisers 2 QAOA for combinatorial optimisation problems 3 Parameterised quantum circuits and barren plateau problem 4 Quantum kernel methods for classification and regression 5 Quantum neural networks and expressibility 6 Benchmarking quantum advantage claims in ML applications
PennyLane Qiskit Machine Learning TensorFlow Quantum Amazon Braket
Classical simulation limits and quantum advantage boundaries
6 Drug discovery and catalyst design through quantum simulation
Qiskit Nature PennyLane Chemistry OpenFermion PySCF (classical reference)
Step 8 advanced 6-8 weeks
Quantum Simulation Learn how quantum computers simulate quantum systems intractable for classical machines, with applications in chemistry and materials science.
1 Hamiltonian simulation and Trotterisation 2 Molecular ground-state energy calculation with VQE 3 Quantum dynamics simulation for chemical reactions 4 Materials science applications: strongly correlated electron systems 5 Classical simulation limits and quantum advantage boundaries 6 Drug discovery and catalyst design through quantum simulation
Qiskit Nature PennyLane Chemistry OpenFermion PySCF (classical reference)
Quantum internet architecture: trusted nodes, end-to-end entanglement
6 Experimental QKD deployments and satellite-based quantum communication
SimulaQron (quantum network simulator) NetSquid (TU Delft) Qiskit for QKD protocol simulation ID Quantique (commercial QKD reference)
Step 9 advanced 4-6 weeks
Quantum Networking Study quantum communication protocols including QKD, teleportation, and the foundations of a future quantum internet.
1 Quantum key distribution: BB84, E91, and decoy-state protocols 2 Quantum teleportation and entanglement swapping 3 Quantum repeaters, entanglement distillation, and purification 4 Quantum memory requirements and coherence time challenges 5 Quantum internet architecture: trusted nodes, end-to-end entanglement 6 Experimental QKD deployments and satellite-based quantum communication
SimulaQron (quantum network simulator) NetSquid (TU Delft) Qiskit for QKD protocol simulation ID Quantique (commercial QKD reference)
5 Topological qubits: Majorana fermions and Microsoft's approach
6 Comparing platforms: coherence times, gate fidelities, connectivity, and scalability
IBM Quantum (superconducting access) IonQ / Quantinuum (trapped ion access) Xanadu (photonic access via Strawberry Fields) QuEra (neutral atom access via Amazon Braket)
Step 10 advanced 4-6 weeks
Quantum Hardware Understanding Develop a working understanding of quantum hardware platforms, their trade-offs, and the engineering challenges of building quantum processors.
1 Superconducting qubits: transmon design, dilution refrigerators, and microwave control 2 Trapped ion qubits: Paul traps, laser-driven gates, and ion shuttling 3 Photonic quantum computing: linear optics, squeezed states, and boson sampling 4 Neutral atom arrays: optical tweezers, Rydberg interactions, and reconfigurability 5 Topological qubits: Majorana fermions and Microsoft's approach 6 Comparing platforms: coherence times, gate fidelities, connectivity, and scalability
IBM Quantum (superconducting access) IonQ / Quantinuum (trapped ion access) Xanadu (photonic access via Strawberry Fields) QuEra (neutral atom access via Amazon Braket)
5
Benchmarking hybrid vs purely classical performance
6 Quantum software architecture: abstraction layers and cloud quantum APIs
Qiskit Runtime Amazon Braket Hybrid Jobs PennyLane (quantum-classical autodiff) Azure Quantum
Step 11 advanced 4-6 weeks
Hybrid Classical-Quantum Systems Design practical hybrid quantum-classical applications that leverage both paradigms for near-term quantum advantage.
1 Variational algorithms: classical optimiser + quantum circuit feedback loops 2 Problem decomposition: identifying quantum-suitable sub-problems 3 Classical pre- and post-processing for quantum algorithm output 4 Error mitigation techniques for NISQ-era hybrid workflows 5 Benchmarking hybrid vs purely classical performance 6 Quantum software architecture: abstraction layers and cloud quantum APIs
Qiskit Runtime Amazon Braket Hybrid Jobs PennyLane (quantum-classical autodiff) Azure Quantum
5 Quantum computing industry roadmaps from IBM, Google, and Microsoft
6 Building a quantum computing career: research, startups, and enterprise roles
Qiskit Finance / Optimization modules D-Wave (quantum annealing) NVIDIA cuQuantum (GPU simulation) Classiq / Q-CTRL
Step 12 advanced 3-4 weeks
Quantum Applications in Industry Explore real-world quantum computing applications in finance, pharma, logistics, and cybersecurity and understand where quantum advantage is nearest.
1 Finance: portfolio optimisation, Monte Carlo pricing, and risk analysis 2 Pharma: molecular simulation for drug discovery and protein folding 3 Logistics: vehicle routing, supply chain, and scheduling optimisation 4 Cybersecurity: quantum-safe cryptography transition and random number generation 5 Quantum computing industry roadmaps from IBM, Google, and Microsoft 6 Building a quantum computing career: research, startups, and enterprise roles
Qiskit Finance / Optimization modules D-Wave (quantum annealing) NVIDIA cuQuantum (GPU simulation) Classiq / Q-CTRL