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Catalog Description
Examine the fundamentals of collecting, managing, and analyzing data; with consideration for the ethical responsibility of data science and the importance of critical thinking. Offered on the letter-grade basis only.
Instructor Description
Introduction to the theory and practice of data science through a human-centered lens, with emphasis on how design choices influence algorithmic results. Students will gain comfort and facility with fundamental principles of data science including (a) Programming for Data Science with Python (b) Data Engineering (c) Database Systems (d) Machine Learning and (e) Human centered aspects such as privacy, bias, fairness, transparency, accountability, reproducibility, interpretability, and societal implications. Each week’s class is divided into two segments: (a) Theory and Methods, a concise description of theoretical concept in data science, and (b) Tutorial, a hands-on session on applying the theory just discussed to a real-world task on publicly available data. We will use Python for programming and cover Python basics in the beginning of the course. For modules related to databases, we will use PostGre SQL.
Prerequisites
Informatics 301.
Restrictions
For any given registration cycle, enrollment in this class will be restricted to undergraduate Informatics majors through registration period 1. Informatics minors will be permitted to add this class or join the waitlist during period 2. All other students must wait until period 3 to add this class or join the waitlist.