Decoding Politics provides politically-inclined, non-STEM students an introduction to how technology and data science can be used for political analysis. Through this course, students will develop a basic understanding of Python through Jupyter notebook, compile data into meaningful graphics, analyze Twitter and social media, examine machine learning’s role in public policy, and evaluate the nuances of cybersecurity policy. This course meets once a week for two hours and is split between lecture and lab.
The first part of the class will be devoted to a lecture given by one of the facilitators in which any necessary concepts for the lab will be demonstrated. The second half of the class will be laboratory-based, with students completing an assignment related to the lecture. Facilitators will be present in the lab to answer any questions pertaining to the lab. As the course progresses, these labs may be replaced by project work sessions or group meetings. Additionally, course instructors will offer office hours throughout the week so that students may come for help with coding or conceptual questions.
Assignments include in class labs, blog posts, coding assignments, and a final project.
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