Delves into symmetries in physics, covering group theory, perturbation, and quantification.
Covers the essentials of data science, including data handling, visualization, and analysis, emphasizing practical skills and active engagement.
Introduces the Applied Data Analysis course at EPFL, covering a broad range of data analysis topics and emphasizing continuous learning in data science.
Delves into the intersection of physics and data in machine learning models, covering topics like atomic cluster expansion force fields and unsupervised learning.
Covers the fundamentals of data science, the scientific method evolution, the role of a data scientist, and the significance of data as the new oil.
Introduces the basics of machine learning, covering supervised and unsupervised learning, linear regression, and data understanding.
Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.
Explores Singular Value Decomposition and its role in unsupervised learning and dimensionality reduction, emphasizing its properties and applications.
