Introduces students to data science as a profession, as currently practiced and continuing to develop. Presents various elements of the data science life cycle at an introductory level, culminating with a start-to-finish data analysis project. Includes guest lectures from data science practitioners and faculty. Explores real-world examples of ethical issues, bias, and privacy in data science. Survey careers in data science and familiarize students with elements of career development.

Lecture: 3 Lab: 0 Credits: 3

This course introduces the critical concepts and skills in statistical inference, machine learning, and computer programming, through hands-on analysis of real-world datasets from various fields.

Lecture: 3 Lab: 0 Credits: 3

This course introduces the critical mathematical foundation knowledge for data science. Specifically, this course covers the basic topics on linear algebra and discrete math that are most relevant to the data science major.

Prerequisite(s): MATH 251

Lecture: 3 Lab: 0 Credits: 3

This course introduces the critical concepts and skills of ethics and privacy in data science, as well as hands-on implementation of important algorithms. It will cover important concepts of bias and privacy, and the computational strategies to ensure fairness and privacy in a variety of emerging data science applications. The course provided hands-on experience in collecting, analyzing, and modeling data for tackling ethical issues.

Lecture: 3 Lab: 0 Credits: 3

This course introduces mathematical tools from optimization, differential equations, and numerical analysis etc. that are relevant to the data science major.

Prerequisite(s): DS 251

Lecture: 3 Lab: 0 Credits: 3