FALL 2016

DCS 1100. Introduction to Digital and Computational Studies

How are digital tools and computational methods being applied and studied in different fields? How are they catalyzing changes in our daily lives? We will use two case studies to introduce these new tools and methods, and to analyze and evaluate their scholarly and practical applications. The first case study is based on Bowdoin’s own history: how can we use new methods to recreate what Joshua Chamberlain could see at the battle of Gettysburg, and thus better understand the battle and his decisions? Next, we turn to the contemporary, and ask what is identity in the era of social media and algorithms? Students will learn the basics of the Python programming language, introductory spatial analysis with ArcGIS, elementary text and social network analysis, and basic environmental modeling. Assumes no prior knowledge of a programming language.

DCS 2020. Forecasting and Predictions

Computers and the Internet have enabled an explosion in the prediction market where everyone from political consultants to large corporations rely on an ever-increasing amount of data to make predictions that drive their decision making. Examines the topic of predictions through the lens of how it is currently impacting our world. Students learn and apply predictive analytic techniques including traditional time-series analysis, elementary Bayesian statistics, and the design of cutting-edge models through data mining and machine learning. Applications and examples focus on the methods that data analysts use to forecast future events. Readings and discussions model how to assess the quality of those predictions and interrogate the ethics of using forecasts to shape strategy and policy that have real-world implications. Instructor selects thematic content and when pertinent, applies these techniques to the case study of presidential and congressional elections.

Tip sheet for advising students interested in computers and programming