Introduction to Human-Centered Data Science

In this course, students will be introduced to the technical, social, and ethical considerations in the field of data science, including data security, governance, and privacy. Particular focus will be places on data scientists' responsibility to create effective and inclusive solutions that are responsive to the needs, values, and perspectives of people.This course will also introduce the themes and skills that will be developed in subsequent courses. Specifically, students will: learn about trends and advances in data science (e.g., A.I. and cloud computing); beexposed to data cleaning procedures for various types of commonly used data; learn about project lifecycle planning and execution; and will learn about the steps in a typical data science project (e.g., question framing, data collection, cleaning, exploration, modeling, interpretation of findings). Moreover, instruction will focus on developing students skills relating to project management, problem framing, communication, and project execution. Students will learn to use various data science tools and techniques to tackle real-world problems. The tools that students will use in this class include the Python programming language, various Python libraries for introductory data analysis and basic visualization, and development environments such as GitHub and Jupyter Notebook.