Federated Learning (FL) is a means to train machine learning models without centralizing data. To deal with the ever-growing demands for training data whilst respecting data privacy and confidentiality, it has become important to move from centralized to federated machine learning. The IBM Federated Learning Community Edition is one means for achieving this goal; it is a platform and library, free to use for non-commercial purposes, with built-in features that facilitate enterprise-strength applications: \url{https://github.com/IBM/federated-learning-lib}. This interactive demo session highlights several featured algorithms available only in the IBM Federated Learning Community Edition, and provides tutorials, audience-interactive examples, and a guest speaker from the tech company Persistent Systems who has used the IBM Federated Learning Community Edition for Covid-19 outcome prediction for hospitals.