Tutorials

The following tutorials demonstrate examples of how Covalent is used in real-world settings. Make sure you have properly installed Covalent and have started the Covalent server before attempting to reproduce a tutorial.

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Beginner

Topic	Title
Machine learning	MNIST classifier
Machine learning	Using Covalent with PennyLane for hybrid computation
Machine learning	Linear and convolutional autoencoders
IBM Quantum Cloud	Accessing IBM Quantum Cloud

Intermediate

Topic	Title
Machine Learning	Iris classification
Machine Learning	Variational parity classification
Machine Learning	Modeling time series for sales forecasting
Machine Learning	Training a quantum-classical neural network
Quantum Chemistry	Dynamic quantum chemistry workflow

Advanced

Topic	Title
Quantum Chemistry	Simulating the Nitrogen-Copper interaction
Machine Learning	Classical and quantum support vector machines
Machine Learning	Training quantum embedding kernels for classification
Quantum Optimization	Using QAOA to Solve the Max-Cut Problem
Machine Learning	Quantum Ensemble Classification
Astronomy	Tracking stars in the night sky
Quantum Gravity	Classifying discrete spacetimes by dimension
Generative AI/LLM	Scalable API backends for LLM and generative AI
Federated learning	Federated learning

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Do you use Covalent in an interesting project? Contribute a tutorial on GitHub. To get started, check out the Tutorial Guidelines.