ADA 201: Principles and Techniques of Data Analytics I

Goal: Data Analytics combines data, computation and inferential thinking to solve challenging problems and understand their intricacies. This class explores key principles and techniques of data science, and teaches students how to create informative data visualizations. It also explores particular concepts of Linear Algebra which are central to Data Science.
Content: By the end of this course, students will be able to: Understand and use linear algebra principles to derive prediction algorithms; Effectively collect, sample, clean and analyze data sets; Understand the fundamental principles of Regression Analysis; Use SQL, RegEx, Pandas, and Pytorch to solve data analysis problems; Build effective data visualizations.
Prerequisite(s): ADA 102, MAT 205, MAT 210, CSC 216, CSC 218.
Credit: 3
Degree Level: Undergraduate