Data Science

This workshop is a four-part introductory series that will teach you R from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the open-sourced R Studio software, understand data and basic manipulations, import and subset data, explore and visualize data, and understand the basics of automation in the form of loops and functions. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research.

This two-part workshop introduces students to scikit-learn, the popular machine learning library in Python, as well as the auto-ML library built on top of scikit-learn, TPOT. The focus will be on scikit-learn syntax and available tools to apply machine learning algorithms to datasets. No theory instruction will be provided.

There is enormous interest in building a better understanding of how evidence and data can inform policy. New possibilities have opened up to enable data to be shared and used across states and agencies. One is a technical approach – the Administrative Data Research Facility – which provides a secure environment within which education, training, and workforce data can be shared across agencies and states. The other is human – the Applied Data Analytics training program – which trains government agency staff how to combine and use the data to serve their agency missions. Over 650 participants from over 150 agencies have participated and produced new products and new networks in the process. This presentation discusses the approach sponsored by the California Department of Social Services, joint with the Department of Education and the Economic Development Department. The D-Lab worked with the Coleridge Initiative to successfully combine the two approaches. The presentation will also address the broader vision of how approaches like this can serve to democratize data for the United States.

This three-part workshop series will prepare participants to move forward with research that uses text analysis, with a special focus on humanities and social science applications.