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.
Delves into the intersection of physics and data in machine learning models, covering topics like atomic cluster expansion force fields and unsupervised learning.
Explores Big Data generation, storage, processing, and dimensions, along with challenges in data analytics, cloud computing elasticity, and security.
Covers Spark Data Frames, distributed collections of data organized into named columns, and the benefits of using them over RDDs.
Covers the essentials of data science, including data handling, visualization, and analysis, emphasizing practical skills and active engagement.
