ADA 101: Foundations of Data Analytics I

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. Particular attention will be paid to Bayes’ Theorem - one of the most important concepts in applying statistics to the real world. Lastly, this course will cover the implications and dangers of bias in data.
Content: This course teaches students the fundamentals of Data Analytics and Science. By the end of this course, students will be able to: Use industry-standard tools (Python, Anaconda, Jupyter Notebooks); Analyze large data sets; Test hypotheses on datasets; Present data-driven results in a clear manner; Describe the current landscape of the Data Science industry; Recognize examples (and limitations) of Machine Learning in day-to-day life; Articulate and use Bayes’ Rule; Understand the implications of bias in data.
Prerequisite(s): MAT 220 Statistics.
Credit: 3
Degree Level: Undergraduate