- Welcome to Data Science and the Mind!
How does the human mind work? We explore this question by analyzing a range of data concerning such topics as human rationality and irrationality, human memory, how objects and events are represented in the mind, and the relation of language and cognition. This class provides young scientists with critical thinking and computing skills that will allow them to work with data in cognitive science and related disciplines.
This connector connects with the Foundations of Data Science course in two ways: 1) it applies and reinforces inferential and computing ideas from the main course to quantitative analysis of phenomena in cognitive science 2) it connects practical skills taught in the main course with hypothesis- and theory-driven goals.
Specifically, the structure of this connector is designed to follow the contents of the main course in order to apply and reinforce learned concepts and skills – with increasing depth – to cognitive science. For example, ideas taught earlier in the main course such as data visualization, histogram, and sampling would be introduced initially in this connector with focused applications to cognitive phenomena – a small 1-2-week lag is introduced between the connector and main courses so that concepts acquired from the main course can be reinforced in the connector. More sophisticated techniques from the main course such as regression and predictive modeling would also be introduced later in the connector, hence providing students with recurrent opportunities of practice.
Complementing the data-driven (bottom-up) approach in the main course, this connector course introduces students with goal-directed, hypothesis- and theory-driven (top-down) approaches to cognitive problems. Concretely, each session (as listed in the syllabus section) is aimed at exploring a question or a theme that concerns the nature of the mind, and the reading materials would provide a case study that exemplifies how such a question can be approached and tested against data.
Instructor: Yang Xu