Delves into the intersection of physics and data in machine learning models, covering topics like atomic cluster expansion force fields and unsupervised learning.
Explores data handling fundamentals, including models, sources, and wrangling, emphasizing the importance of understanding and addressing data problems.
Addresses gender equality challenges in engineering, focusing on statistics and solutions for improving women's representation and opportunities in the field.
