Data Science Fundamentals

This lecture introduces the fundamentals of data science, emphasizing the exponential growth of data volume, variety, and the need for structured methods in data analysis. It covers the scientific method evolution from hypothesis-driven to data-driven approaches, highlighting the importance of exploring, modeling, and communicating results. The lecture also discusses the role of a data scientist in obtaining, cleaning, modeling, and interpreting data, blending hacking, statistics, and machine learning. Furthermore, it delves into the significance of data as the new oil and the effectiveness of large-scale statistical language modeling in machine translation.