How to: Privacy Learning Resources
[Differential Privacy Blog Series by the National Institute of Standards and Technology(NIST)](https://www.nist.gov/itl/applied-cybersecurity/privacy-engineering/collaboration-space/focus-areas/de-id/dp-blog)

[Apple's Differential Privacy Overview](https://www.apple.com/privacy/docs/Differential_Privacy_Overview.pdf)

[Learning with Privacy at Scale with Apple Machine Learning](https://machinelearning.apple.com/research/learning-with-privacy-at-scale)

[Microsoft Research Differential Privacy Overview](https://www.microsoft.com/en-us/research/publication/differential-privacy/)

[Responsible Machine Learning with Microsoft Azure](https://azure.microsoft.com/en-us/services/machine-learning/responsibleml/)

[Responsible AI Resources with Microsoft AI](https://www.microsoft.com/en-us/ai/responsible-ai-resources)

[Preserve data privacy by using differential privacy and the SmartNoise package](https://docs.microsoft.com/en-us/azure/machine-learning/concept-differential-privacy)

[Open Differential Privacy(OpenDP) Initiative by Microsoft and Harvard](https://projects.iq.harvard.edu/opendp)

[Google's Differential Privacy Library](https://github.com/google/differential-privacy)

[Computing Private Statistics with Privacy on Beam from Google Codelabs](https://codelabs.developers.google.com/codelabs/privacy-on-beam/#0)

[Introducing TensorFlow Privacy: Learning with Differential Privacy for Training Data](https://blog.tensorflow.org/2020/06/introducing-new-privacy-testing-library.html)

[TensorFlow Federated: Machine Learning on Decentralized Data](https://www.tensorflow.org/federated/)

[Federated Analytics: Collaborative Data Science without Data Collection](https://ai.googleblog.com/2020/05/federated-analytics-collaborative-data.html)

[Differentially-Private Stochastic Gradient Descent(DP-SGD)](https://github.com/tensorflow/privacy/blob/master/tutorials/walkthrough/README.md)

[Learning Differential Privacy from Harvard University Privacy Tools Project](https://privacytools.seas.harvard.edu/differential-privacy)

[Harvard University Privacy Tools Project Courses & Educational Materials](https://privacytools.seas.harvard.edu/courses-educational-materials)

[The Weaknesses of Differential Privacy course on Coursera](https://www.coursera.org/lecture/data-results/weaknesses-of-differential-privacy-50Y9k)

[The Differential Privacy of Bayesian Inference](https://privacytools.seas.harvard.edu/publications/differential-privacy-bayesian-inference)

[Simultaneous private learning of multiple concepts](https://privacytools.seas.harvard.edu/publications/simultaneous-private-learning-multiple-concepts)

[The Complexity of Computing the Optimal Composition of Differential Privacy](https://privacytools.seas.harvard.edu/publications/complexity-computing-optimal-composition-differential-privacy)

[Order revealing encryption and the hardness of private learning](https://privacytools.seas.harvard.edu/publications/order-revealing-encryption-and-hardness-private-learning)

[SAP HANA data anonymization using SAP Software Solutions](https://www.sap.com/cmp/dg/crm-xt17-ddm-data-anony/index.html)

[SAP HANA Security using their In-Memory Database](https://www.sap.com/products/hana/features/security.html)

[DEFCON Differential Privacy Training Launch](https://opensource.googleblog.com/2020/08/defcon-differential-privacy-training.html)

[Secure and Private AI course on Udacity](https://www.udacity.com/course/secure-and-private-ai--ud185)

[Differential Privacy - Security and Privacy for Big Data - Part 1 course on Coursera](https://www.coursera.org/learn/security-privacy-big-data)

[Differential Privacy - Security and Privacy for Big Data - Part 2 course on Coursera](https://www.coursera.org/learn/security-privacy-big-data-protection)

[Certified Ethical Emerging Technologist Professional Certificate course on Coursera](https://www.coursera.org/professional-certificates/certified-ethical-emerging-technologist)