Merge pull request #4 from maddox-j/dlai-fl-course

Add Indaba notebook and Flower DL.ai course

README.md

@@ -32,11 +32,14 @@ Please find below all the contributed resources, organised by category
 
 ### Tutorials
 
+* [From Centralised to Decentralised Training: An Intro to Federated Learning](https://github.com/deep-learning-indaba/indaba-pracs-2024/tree/main/practicals/Federated_Learning) - A Jupyter Notebook tutorial aimed to provide a practical overview with code examples to all the the foundational concepts tackled in federated learning. This tutorial was written by Andrej Jovanović, Sree Harsha Nelaturu and Luca Powell and presented at the 2024 iteration of the Deep Learning Indaba. 
+
 * [SyftBox | #30DaysOfFLCode](https://syftbox-documentation.openmined.org/) - The new project by [OpenMined](https://openmined.org) that aims to make privacy-enhancing technologies more accessible and user-friendly for developers.
+
     * [SyftBox Computational Model](https://syftbox-documentation.openmined.org/computation-model) - How computation works on SyftBox, in a nutshell
     * [Federated CPU Tracker Member (part1)](https://syftbox-documentation.openmined.org/cpu-tracker-1) - An example of SyftBox API that monitors local CPU usage and shares a private/sanitized version of the data within the SyftBox federated network.
     * [Federated CPU Tracker Leader (part 2)](https://syftbox-documentation.openmined.org/cpu-tracker-2) - A SyftBox API that aggregates CPU data from all members contributing to the computation, and creates a live visualization dashboard.
-    
+
 ### Articles
 
 * [Beyond Privacy Trade-offs with Structured Transparency](https://arxiv.org/abs/2012.08347) - Structured Transparency: a five-part framework to combine multiple PETs, such as secure computation and federated learning, to maximise their value, and to reduce lingering use-misuse trade-offs in multiple domains.
@@ -51,6 +54,8 @@ Federated learning involves training statistical models over remote devices or s
 
 * [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 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.