Limited-Time Offer: Up to 75% Off Coursera Plus!
7000+ certificate courses from Google, Microsoft, IBM, and many more.
This course aims to provide a holistic, high-dimensional perspective on extracting and encoding information in complex chemical systems. The learning outcomes include understanding how to extract features from simulation data, encode high-dimensional information into a lower-dimensional representation, and analyze multiscale spatiotemporal correlations in chemical systems. The course teaches skills such as interpreting simulation data, identifying relationships in energy landscapes, and selecting features for analysis. The teaching method involves a presentation by Aurora Clark focusing on the challenges and opportunities in this active research area. The intended audience for this course includes researchers, scientists, and professionals interested in computational chemistry, chemical simulations, and data analysis in complex systems.
