DATA 73500 Working with Data Fall 2020

About This Course

This course covers the fundamentals of working with data. Students will be introduced to key disciplines that provide techniques used for working with small, medium and big data today—classical statistics, contemporary data science, machine learning, and data visualization. They will learn about different data types; what constitutes a valid dataset that can be analyzed quantitatively; how data should be formatted to create a valid dataset. The course will also explore fundamental theoretical questions that arise when we attempt to represent social or cultural phenomena as data. Particular attention will be focused on working with social network services data, user generated content, and other types of data about societies and individuals that have emerged recently (such as sensor data) and massive media datasets (images, video, text, sound, code, etc.). The course will explore fundamental database technologies and more recent techniques for working with real-time data flows.

The “data revolution” has transformed the way we understand and interact with the world around us. The availability of large datasets, progress in computer hardware and software, and use of the web to share data and acquire it from numerous sources (including social network services, libraries, museums, city governments, non-profits, etc.) has created many new possibilities in many fields including computer science, social science, humanities, business, economics, and medicine. These developments have also led to the emergence of a number of new research fields in the end of 2000s: social computing, computational social science, digital humanities, cultural analytics, and culturomics. This course introduces students to fundamental concepts and practical techniques and skills needed to work with data.

We’ll begin with a broader examination of data and society. Then, we’ll take a look at some of the tools used by data analysts and data scientists to produce knowledge in various settings. We’ll focus mainly on analysis of text in our coding work; this is the best place to begin to understand the choices we make as researchers and analysts in applied settings.

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