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 ## Learning
 
 - [IBM Q Full User Guide](https://quantumexperience.ng.bluemix.net/qx/tutorial?sectionId=full-user-guide&page=introduction) - Short tutorials providing a gentle introduction to quantum computing and IBM Q.
-- [Nielsen and Chuang](http://quantum.wobblybit.com/category/nielsenchuang/) - Worked examples on quantum algorithm problems.
+- [Nielsen and Chuang](http://quantum.wobblybit.com/category/nielsenchuang/) - Worked examples on quantum algorithm problems
+- [Documentation for Forest and pyQuil](http://pyquil.readthedocs.io/en/latest/) - Tutorials for Rigetti Computing's SDK.
 
 ## Development Tools
 
 - [IBM Quantum Composer](https://quantumexperience.ng.bluemix.net/qx/editor) - Online quantum composer to run experiments on real quantum computing hardware.
 - [QISKit SDK](https://github.com/QISKit/qiskit-sdk-py) - Software development kit for working with OpenQASM and the IBM Q Experience.
 
+- [pyQuil](https://github.com/rigetticomputing/pyquil) - A Python library for quantum programming using Quil.
+
 ## Books
 
 - [Quantum Computation and Quantum Information](https://books.google.com/books/about/Quantum_Computation_and_Quantum_Informat.html?id=-s4DEy7o-a0C&redir_esc=y) - A well appreciated comprehensive textbook for those with a bit of prior knowledge in maths, computer science and physics.
+- [Quantum Computing for Computer Scientists](https://www.amazon.com/Quantum-Computing-Computer-Scientists-Yanofsky/dp/0521879965) - This textbook teaches quantum computing using an approach that is accessible to undergraduate computer science students.