course
PennyLane Codebook: Interactive Quantum ML Learning
Xanadu / PennyLane Team
PennyLane
5 courses · 27 tutorials
Courses
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course
Xanadu Quantum Codebook
Xanadu
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course
PennyLane Quantum Machine Learning Demos
Xanadu / Community
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QHack 2024: Quantum Machine Learning Challenge Course
Xanadu / QOSF Community
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course
Amazon Braket Learning Plan and Digital Badge (AWS Skill Builder)
AWS Quantum Technologies team
Free Tutorials
- →
- advanced
- 35 min
Diagnosing and Avoiding Barren Plateaus in PennyLane
Understand why barren plateaus occur in deep variational circuits, how to detect them in PennyLane, and practical strategies to avoid them including layerwise training and structured ansatze.
- →
- advanced
- 35 min
Compiling Quantum Programs with PennyLane Catalyst
Use PennyLane Catalyst to JIT-compile hybrid quantum-classical programs with JAX, enabling fast execution on both simulators and quantum hardware.
- →
- intermediate
- 30 min
Finite-Shot Optimization in PennyLane
Optimize variational circuits using finite shots in PennyLane. Compare parameter-shift, SPSA, and natural gradient estimators for shot-limited hardware settings.
- →
- beginner
- 12 min read
PennyLane Hello World
Run your first differentiable quantum circuit in PennyLane. Build a Bell state, compute gradients, and see why PennyLane is the go-to framework for quantum ML.
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- advanced
- 40 min
Active Space Methods for Quantum Chemistry in PennyLane
Reduce molecular simulation cost by selecting active orbitals in PennyLane. Combine active space selection with VQE for accurate molecular ground state energies.
- →
- intermediate
- 30 min read
Quantum Kernels and Support Vector Machines with PennyLane
Learn how to build quantum kernel functions with PennyLane, use them with scikit-learn's SVM, and understand when quantum kernels might offer an advantage over classical kernels, with a full working classification example.
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- intermediate
- 20 min read
Quantum Machine Learning with PennyLane: Your First Classifier
Build a quantum classifier using PennyLane's parameterized circuits and train it to classify a simple dataset using gradient descent.
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- advanced
- 35 min
Quantum Natural Gradient in PennyLane
Implement quantum natural gradient descent in PennyLane using the quantum Fisher information matrix. Compare convergence against standard gradient descent on a VQE benchmark.
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- intermediate
- 25 min
Shot-Adaptive Optimization in PennyLane
Use PennyLane's shot-adaptive optimizer to allocate measurement shots intelligently across circuit parameters.
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- intermediate
- 25 min read
Variational Quantum Eigensolver with PennyLane
Implement the Variational Quantum Eigensolver to find the ground state energy of a hydrogen molecule using PennyLane and gradient-based optimization.
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- intermediate
- 25 min read
QAOA: Quantum Approximate Optimisation Algorithm with PennyLane
Implement the Quantum Approximate Optimisation Algorithm to solve the MaxCut graph problem using PennyLane, and understand how QAOA bridges quantum computing and combinatorial optimisation.
- →
- advanced
- 45 min
Quantum GANs with PennyLane
Build a quantum generative adversarial network in PennyLane with a quantum generator and classical discriminator.
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- intermediate
- 22 min read
Noise and Error Mitigation in PennyLane
Understand how noise affects quantum circuits in the NISQ era and implement zero-noise extrapolation (ZNE) and probabilistic error cancellation using PennyLane.
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- intermediate
- 15 min read
QAOA for Max-Cut with PennyLane
Implement the Quantum Approximate Optimization Algorithm for the Max-Cut problem in PennyLane: graph encoding, cost Hamiltonian, circuit construction, and parameter optimization.
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- advanced
- 16 min read
Quantum Chemistry with PennyLane
Use PennyLane's quantum chemistry module to build molecular Hamiltonians, construct UCCSD circuits, and run VQE to find ground state energies.
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- advanced
- 70 minutes
Quantum Generative Adversarial Networks with PennyLane
Implement a patch quantum GAN in PennyLane with a parametric quantum generator and classical neural network discriminator. Covers adversarial training, mode collapse, and how entanglement contributes to output diversity.
- →
- advanced
- 16 min read
Quantum Transfer Learning with PennyLane
Combine a classical pre-trained CNN with a parameterized quantum circuit for image classification using PennyLane's quantum transfer learning technique.
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- intermediate
- 16 min read
Introduction to Quantum Machine Learning
A conceptual and practical introduction to quantum machine learning: what QML is, data encoding strategies, parameterized quantum circuits, and a complete classification example.
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- intermediate
- 12 min read
Quantum Teleportation with PennyLane
Implement quantum teleportation in PennyLane: creating the entangled pair, Bell measurement, classical correction, and verifying the teleported state.
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- intermediate
- 50 minutes
Building a Variational Quantum Classifier from Scratch
Build a complete binary quantum classifier with angle encoding, strongly entangling layers, BCE loss, and Adam optimizer, trained on the moons dataset, with decision boundary visualization and comparison to logistic regression.
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- advanced
- 60 minutes
Decomposing Arbitrary Gates into Clifford+T with PennyLane
Understand why Clifford+T is the universal fault-tolerant gate set, the cost of T gates in magic state distillation, and how to analyze T-count with PennyLane.
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- advanced
- 70 minutes
Lithium Hydride VQE with PennyLane: From Molecule to Energy
Full VQE for LiH using PennyLane's qchem module: molecular Hamiltonian, Hartree-Fock initial state, UCCSD ansatz, optimization, and potential energy surface scan.
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- advanced
- 75 minutes
Adaptive Variational Circuits with ADAPT-VQE in PennyLane
Implement a simplified ADAPT-VQE algorithm in PennyLane. Build an operator pool, greedily select operators by gradient magnitude, grow the ansatz iteratively, and compare convergence against fixed UCCSD for the H2 molecule.
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- advanced
- 70 minutes
Noise-Aware Training for Variational Quantum Circuits
Train variational quantum circuits directly on realistic noise models using PennyLane. Compare circuits trained with and without noise, insert depolarizing and amplitude damping channels, and apply noise injection techniques to improve real hardware performance.
- →
- intermediate
- 17 min read
Hybrid Quantum-Classical Optimization Loops with PennyLane and PyTorch
Build a complete hybrid quantum-classical optimization pipeline: PennyLane QNode wrapped as a PyTorch layer, automatic differentiation through quantum circuits, Adam optimizer training on a binary classification task, and comparison to classical logistic regression.
- →
- intermediate
- 20 min read
Using PennyLane with Amazon Braket
Connect PennyLane to Amazon Braket backends to run hybrid quantum-classical workflows, from local simulation to IonQ trapped-ion hardware.
- →
- advanced
- 40 minutes
High-Performance Simulation with PennyLane Lightning and GPU
Explore PennyLane's Lightning family of high-performance simulation backends, learn how to use adjoint differentiation for efficient gradient computation, and understand when to deploy lightning.qubit, lightning.gpu, and lightning.kokkos.