Introduction to Applied Data Science

(3 Credits)

This course provides an introduction to Urban Data Science, focusing on the application of data analytics in urban contexts. The course will explore a range of data handling techniques, from data curation and collection to preprocessing and cleaning. Key topics include exploratory data analysis (EDA), hypothesis testing, and handling randomness in data. The course also covers essential statistical techniques like linear and logistic regression, covering topics including out-of-sample evaluation techniques and regularized regression. Practical case examples will illustrate the concepts, preparing students to tackle real-world urban data challenges.