Dig into Data Science Across Disciplines!

January 15, 2019
This semester's Connector courses offer Data 8 students the opportunity to explore data science in a variety of disciplines, from physics to literature to child nutrition in the developing world. Learn more about some of the offerings below, click here to find out more about Connectors, and go here for a listing of all Spring 2019 options. 

Connectors with availability for Spring 2019

Data Science Applications in Physics

Yury Kolomensky - PHYSICS 88 Class #: 27035 - M 2-4 Evans 60
Introduction to data science with applications to physics. Topics include: statistics and probability in physics, modeling of the physical systems and data, numerical integration and differentiation, function approximation. Connector course for Data Science 8, room-shared with Physics 77. Recommended for freshmen intended to major in physics or engineering with emphasis on data science.

Children in the Developing World

Sarah Reynolds - L&S 88-1 Class #: 26918 - M 3-6pm Cory 105 - 3 units
Child nutrition and education are important for adult success, but children in developing countries fall behind with nutritional consumption and have fewer educational opportunities. Household surveys are an instrumental tool for understanding factors associated with investments in children. We will use household data sets to explore relationships between nutrition and education outcomes and a variety of socio-economic variables to establish an understanding of contextual elements which can hinder or promote child growth and learning.

Reading and Writing the Digital Age

Hannah Zeavin - ENGLISH 98Class #: 33111 - M 11am-1pm Cory 105  - 2 units
In this course, we will survey the production, consumption, and study of literary texts in the digital age. We will explore digital culture in social and networked practices of writing and reading, new theories of reading in the digital moment (distance reading, surface reading), and debates within the digital humanities, media and literary studies, including theorists Best, Chun, Gitelman, Hayles, Liu, Love, and Marcus. Moving from Internet 1.0 to Internet 2.0, we will engage many “born-digital” and online texts, such as Michael Joyce’s afternoon, William Gibson’s Aggripa, Claudio Pinhanez’s “Open Diary” as well as digital literary platforms and websites. We will conclude the semester by looking at digital writing and its reception now, including the Instagram poetry of Rupi Kaur and Warsan Shire’s poetics in Beyoncé’s Lemonade.

Reproducibility and Open Science

Eric Van Dusen -  L&S 88-2 Class #: 26919  M 1-3pm Cory 105 -  2 units
The purpose of this course is to introduce students to the issues of scientific reproducibility and highlight some recent examples in the scientific literature. The class will present and cover different tools and concepts used in open science.  In this course, Data Science students across domains will be introduced to concepts in scientific reproducibility and transparency through readings, case-studies, and hands-on lab activities. The course is intended as a survey of topics for students who have taken or are currently enrolled in Data 8. Students in the course will learn about the principles of doing open science, be able to create their own reproducible workflows, and gain an introduction to computational tools for Reproducible Data Analysis