CSCI 3343 Introduction to Data Science

This course provides an introduction to computational and statistical approaches to analyzing data. We cover six main topics in the course: (i) Data and distributions, (ii) Statistical inference, (iii) Assessing the relationships between variables, (iv) Supervised and unsupervised learning, (v) Dimensionality reduction, and (vi) Networks. While this course will substantially overlap with courses such as introductory statistics, data mining, and machine learning, it will be distinct in the following ways: emphasis on conceptual understanding of hypothesis testing and statistical considerations; emphasis on visualization as a tool for gaining insights into possible biases in the data, patterns in data, and conclusions derived from data; and emphasis on the use of computational thinking to overcome statistical difficulties.

Credits

3

Prerequisite

CSCI 2380 and CSCI 3310.

Schedule Type

Lecture

Grading Basis

Standard Letter (A-F)

Administrative Unit

Department of Computer Science

Offered

As scheduled