DATA 1000

This course is designed to provide students with the foundational skills needed for data analysis and visualization using a programming language such as Python. Topics include handling and manipulating data structures, cleaning and preparing datasets, and visualizing data to develop insights. There will also be an exploration of core data structures, and key data analysis tools such as NumPy, Pandas, SQL, and Matplotlib. Data Preprocessing, Feature Engineering, and Basic Modeling as well as techniques for handling missing data; scaling and normalization; feature selection and encoding categorical data will be studied. Some basic machine learning algorithms will be discussed. [Department(s): Department of Mathematics and Statistics]