Covers the essentials of data science, including data handling, visualization, and analysis, emphasizing practical skills and active engagement.
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.
Delves into the intersection of physics and data in machine learning models, covering topics like atomic cluster expansion force fields and unsupervised learning.
