Embedding software engineering best practices into AI projects with Kedro
In this talk, I will explore how software engineering best practices such as modularity, separation of concerns, testability, and reproducibility can elevate the quality and deployability of AI projects. Focusing on the Kedro framework, I’ll uncover how these principles seamlessly integrate into data workflows, making complex projects more manageable and scalable. This session is designed for data practitioners interested in adopting robust software engineering methodologies in their work. Attendees will gain practical insights into improving project design, ensuring code quality, and facilitating smoother transitions to production environments. No extensive software engineering background is required, making this an accessible and informative session for all data professionals looking to enhance their knowledge of software principles through Kedro.
