SE 422 | Introduction to Data Science 2526F | Gökçen Tonbul

This course is an applied introduction to Python for core data science tasks, including data scraping, manipulation, and visualization. You'll cover the foundational use of vectors and matrices and review essential statistical concepts such as conditional probability, Bayes' theorem, and the normal distribution. The final module investigates core machine learning techniques for model building, specifically focusing on prediction, regression, classification, and clustering.