UVADLC Notebooks is a collection of Jupyter notebook tutorials designed for teaching a deep learning course at the University of Amsterdam.
The repository addresses the need for comprehensive, hands-on learning materials in deep learning by providing structured notebook tutorials that cover core concepts and practical implementations. The tutorials are built around frameworks including PyTorch, PyTorch Lightning, JAX, Flax, and Optax, allowing students to learn both foundational theory and modern implementation patterns across different deep learning ecosystems.
The material suits students and practitioners seeking university-level instruction in deep learning with working code examples. The notebooks are particularly valuable for those wanting to understand implementations in multiple frameworks rather than being locked into a single approach. The collection covers the breadth expected in a graduate-level AI course, making it useful both as a structured curriculum and as a reference for specific topics.
The project maintains active engagement with its educational mission, with notebooks regularly updated to reflect current best practices in the frameworks it covers. The codebase demonstrates consistent attention to keeping examples functional across framework versions and adding new material to address emerging techniques in deep learning.
