ADA 102: Foundations of Data Analytics II

Goal: In an increasingly data-driven world, everyone should be able to understand the numbers that govern so much of our lives. Students will learn the core concepts of inference, data analysis and computing by working with real economic, social and geographic data. This course will also provide students with an introduction to the applications of Data Analytics in the workforce, with specific attention paid to the role of the Data Scientist or Analyst, and to the application of Big Data.
Content: By the end of this course, students will be able to: Deploy A/B testing to meet business objectives; Understand how to design a range of data-driven experiments; Use basic machine learning - including linear regression and classification; Use data to update predictions; Understand the difference between correlation and causality, and how to identify either relation using data; Define Big Data and understand its importance to Business Analytics; Articulate the role of a data scientist or analyst within the workforce
Prerequisite(s): ADA 101.
Credit: 3
Degree Level: Undergraduate