Merge pull request #6 from snehilsanyal/main

Added base paper, blog, cartoon and a short course

README.md

@@ -51,13 +51,19 @@ Federated learning involves training statistical models over remote devices or s
 
 * [Advances and Open Problems in Federated Learning](https://arxiv.org/abs/1912.04977) - Federated learning (FL) is a machine learning setting where many clients collaboratively train a model under the orchestration of a central server, while keeping the training data decentralized. Motivated by the explosive growth in FL research, this paper discusses recent advances and presents an extensive collection of open problems and challenges.
 
+* [Communication-Efficient Learning of Deep Networks from Decentralized Data](https://proceedings.mlr.press/v54/mcmahan17a/mcmahan17a.pdf) - First paper on Federated Learning by McMahan et. al. Google Inc. This paper introduces the term Federated Learning, runs experiments on MNIST and CIFAR Datasets, and also introduces the famous aggregation algorithm FedAverage. Check out the blog based on the paper here: [Federated Learning: Collaborative Machine Learning without Centralized Training Data](https://research.google/blog/federated-learning-collaborative-machine-learning-without-centralized-training-data/)
+
+* [An online comic on Federated Learning, by Google AI](https://federated.withgoogle.com/) - Google AI came up with this fun online comic on Federated Learning which is a great resource for beginners starting their journey in the field of Federated Learning. Great for building up the motivation to learn FL.
+
 
 ### Courses
 
 * [The Private AI Series](https://courses.openmined.org/) - Learn how privacy technology is changing our world and how you can lead the charge.
 
 * [Federated Learning @ DeepLearning.AI](https://www.deeplearning.ai/short-courses/intro-to-federated-learning/) - An introductory course on federated learning delivered by DeepLearning.AI in collaboration with Flower.
 
+* [Federated Fine-tuning of LLMs with Private Data @ DeepLearning.AI x Flower Labs](https://learn.deeplearning.ai/courses/intro-to-federated-learning-c2)- Part 2 of the Intro to Federated Learning course delivered by DeepLearning.AI and Flower Labs.
+
 * [Federated Learning Tutorial @ NeurIPS 2020](https://drive.google.com/file/d/1QGY2Zytp9XRSu95fX2lCld8DwfEdcHCG/view) - Federated Learning Tutorial @ NeurIPS 2020
 
 * [Secure and Private AI](https://www.udacity.com/course/secure-and-private-ai--ud185) - Learn skills to build AI systems that prioritize security and privacy using cutting-edge techniques. The course introduces tools and methods for securely handling sensitive data in AI applications, including Federated Learning, Differential Privacy, and Encrypted Computation.