2018 - 2019
Many of the most pressing problems in the world can be addressed with data. We are awash in data and modern citizenship demands that we become literate in how to interpret data, what assumptions and processes are necessary to analyze data, as well as how we might participate in generating our own analyses and presentations of data. Consequently, data analytics is an emerging field with skills applicable to a wide variety of disciplines. This course introduces analysis, computation, and presentation concerns through the investigation of data driven puzzles in wide array of fields – political, economic, historical, social, biological, and others. No previous experience is required.
The Data Analytics colloquium involves three central learning components. 1) regular engagement with guest presentations and community activities in data analytics, 2) group discussion featuring critical analysis and connection of themes found in the guest presentations and in related data analytics topics, and 3) preparation and refinement of professional communication skills necessary for the required internship component of the data analytics major. This course provides an opportunity for students to connect on data analytics ideas and applications, using a range of perspectives that may or may not be normally encountered in a traditional course. Students will develop the knowledge, skills, and methods they need to progress to more advanced learning, while also creating bridges with members of the data analytics community within and outside of Denison. The course must be taken twice by majors: once as a sophomore, and again as either a junior or senior.
Prerequisite(s): DA 101 (may be taken concurrently).
Utilizing Denison as a model of society, this practicum set in a seminar will explore questions of collective import through the analysis of new and existing sources of data at Denison. A problem-driven approach will lead to the acquisition of new, appropriate data analytic skills, set in an ethical context that carefully considers the implications of data display and policy recommendations on community members. A significant component of the course is working with policymaking and implementing professionals on campus and developing presentation skills appropriate for professional communication with the public. Though a significant learning opportunity itself, this course should also be seen as a prelude to a community internship in the post-Junior year summer.
Prerequisite(s): DA 101, CS 181 and MATH 220, or consent of instructor.
This course is designed to develop students' understanding of the cutting edge methods and algorithms of data analytics and how they can be used to answer questions about real-world problems. These methods, and the underlying models, can be used to learn from existing data to make predictions about new data. The course will examine both supervised and unsupervised methods and will include topics such as clustering, classification, and network analysis.
Prerequisite(s): CS 181 and MATH 220 or consent of instructor.
This is a capstone seminar for the Data Analytics major in which students work collaboratively on research projects. Problems may drive from internship experiences, courses of study at Denison, or other sources subject to instructor approval. Heavy emphasis will be placed on providing ongoing research reports and collective problem solving and review.
Prerequisite(s): DA 301, DA 350 (may be taken concurrently), a disciplinary research methods course, a DA internship, and senior status.