The practice of data science rests upon computing environments that foster responsible uses of data and reproducible scientific inquiries. This course develops students’ ability to engage in data science work using modern workflows, open-source tools, and ethical practices. Students will learn how to author a scientific report written in a lightweight markup language (e.g., markdown) that includes code (e.g., R), data, graphics, text, and other media. Students will also learn to reason about ethical practices in data science.

The practice of data science rests upon computing environments that foster responsible uses of data and reproducible scientific inquiries. This course develops students’ ability to engage in data science work using modern workflows, open-source tools, and ethical practices. Students will learn how to author a scientific report written in a lightweight markup language (e.g., markdown) that includes code (e.g., R), data, graphics, text, and other media. Students will also learn to reason about ethical practices in data science.

The practice of data science rests upon computing environments that foster responsible uses of data and reproducible scientific inquiries. This course develops students’ ability to engage in data science work using modern workflows, open-source tools, and ethical practices. Students will learn how to author a scientific report written in a lightweight markup language (e.g., markdown) that includes code (e.g., R), data, graphics, text, and other media. Students will also learn to reason about ethical practices in data science.

The practice of data science rests upon computing environments that foster responsible uses of data and reproducible scientific inquiries. This course develops students’ ability to engage in data science work using modern workflows, open-source tools, and ethical practices. Students will learn how to author a scientific report written in a lightweight markup language (e.g., markdown) that includes code (e.g., R), data, graphics, text, and other media. Students will also learn to reason about ethical practices in data science.

The practice of data science rests upon computing environments that foster responsible uses of data and reproducible scientific inquiries. This course develops students’ ability to engage in data science work using modern workflows, open-source tools, and ethical practices. Students will learn how to author a scientific report written in a lightweight markup language (e.g., markdown) that includes code (e.g., R), data, graphics, text, and other media. Students will also learn to reason about ethical practices in data science.

The practice of data science rests upon computing environments that foster responsible uses of data and reproducible scientific inquiries. This course develops students’ ability to engage in data science work using modern workflows, open-source tools, and ethical practices. Students will learn how to author a scientific report written in a lightweight markup language (e.g., markdown) that includes code (e.g., R), data, graphics, text, and other media. Students will also learn to reason about ethical practices in data science.

The practice of data science rests upon computing environments that foster responsible uses of data and reproducible scientific inquiries. This course develops students’ ability to engage in data science work using modern workflows, open-source tools, and ethical practices. Students will learn how to author a scientific report written in a lightweight markup language (e.g., markdown) that includes code (e.g., R), data, graphics, text, and other media. Students will also learn to reason about ethical practices in data science.

The practice of data science rests upon computing environments that foster responsible uses of data and reproducible scientific inquiries. This course develops students’ ability to engage in data science work using modern workflows, open-source tools, and ethical practices. Students will learn how to author a scientific report written in a lightweight markup language (e.g., markdown) that includes code (e.g., R), data, graphics, text, and other media. Students will also learn to reason about ethical practices in data science.

This course examines the relationship between female sexuality and nationalism in South Asian cinema, focusing on the crucial role that gender plays in the formation of postcolonial national identities, both on screen and beyond. We will also consider diverse forms of cinematic resistance, especially the work of directors who challenge gender norms. We will look at films from Bollywood and from Bangladesh, Pakistan, Sri Lanka, Nepal, Bhutan, and Afghanistan. We will also have guest-lectures by South Asian activists and filmmakers. (E)

A continuation of RES 331. Prerequisite: RES 331 or equivalent.