.. _tutorials:

Tutorials
=========

A variety of resources are available to help you learn Federated Learning (FL) programming with NVFLARE:

Video Tutorials
---------------

- Quick introductions to FLARE for deep learning and traditional machine learning.
- Examples include CIFAR10 classification and Kaplan-Meier survival analysis.
- `Watch videos and see code <https://nvidia.github.io/NVFlare/>`_

Tutorial Catalog
----------------

- Browse and filter a comprehensive set of examples by experience level, framework, algorithm, application, industry, API, and privacy algorithm.
- `Explore the Catalog <https://nvidia.github.io/NVFlare/catalog/>`_

Feature Tutorials
-----------------

- `POC Tutorials: <https://github.com/NVIDIA/NVFlare/tree/main/examples/tutorials/setup_poc.ipynb>`_
- `Simulator CLI & Python API <https://github.com/NVIDIA/NVFlare/tree/main/examples/tutorials/flare_simulator.ipynb>`_
- `FLARE Python API: Job Submission & Monitoring <https://github.com/NVIDIA/NVFlare/tree/main/examples/tutorials/flare_api.ipynb>`_
- `Logging: Configuration & Customization <https://github.com/NVIDIA/NVFlare/tree/main/examples/tutorials/logging.ipynb>`_
- `NVFlare CLI: Setup, Jobs, Systems, and Deployment <https://github.com/NVIDIA/NVFlare/tree/main/examples/tutorials/nvflare_cli.ipynb>`_
- `Job Recipe: Simplified job creation <https://github.com/NVIDIA/NVFlare/tree/main/examples/tutorials/job_recipe.ipynb>`_

Self-Paced Learning
-------------------

- Extensive materials for self-paced training with NVIDIA FLARE, including detailed tutorials and resources.
- For a comprehensive guide, see the :ref:`self_paced_training` documentation.
- 12-chapter course: in-depth overview of FLARE, covering running federated learning applications, algorithms, system architecture, experimental tracking, system monitoring, and industrial applications.
- Each notebook can be run independently, but sequential learning is recommended.
- Over 100 notebooks and 80 videos: a thorough guide to federated learning with FLARE.

.. note::

   The self-paced training notebooks were developed with NVFlare 2.6. Not all content reflects the latest APIs; some examples may need adjustments for newer versions.