The D3 Spring School welcomes early-stage researchers to join an interdisciplinary spring school at the intersection of machine learning and nutritional science. It focuses on harnessing the power of data-driven approaches to unravel the complex relationships between diet, health, and disease. With recent technological advancements, the program aims to equip junior researchers with specialized computational methods, particularly machine learning algorithms, to extract valuable insights from copious amounts of data generated by modern omics technologies and lifestyle monitoring tools. By fostering collaboration among participants from data science, nutritional science, and related life sciences, the school encourages hands-on training in ML methods and the exploration of their applications in nutrition research. Over four days, the program features keynote talks from renowned international experts and tutorial and coding sessions led by ML specialists. The serene and secluded environment of the Seminarhof Drawehn provides an ideal setting for networking and developing innovative research ideas and collaborations.