Foundations of Data Science

In this course, students will study the Foundations of Data Science from three perspectives: inferential thinking, computational thinking, and real-world relevance. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social issues surrounding data analysis such as privacy and design.

Student Learning Outcomes

At the conclusion of this course, the student should be able to:

1. Employ foundational programming concepts to explore and analyze datasets.
2. Apply foundational data science to explore and analyze datasets.
3. Analyze real-world data sets using a modern programming language, problem decomposition, and code design strategies.
4. Identify limitations and issues surrounding data analysis in terms of bias, ethics, establishing causality, and privacy.

» Learn more about CS 88