Data Analysis

NOTE: See the beginning of Section F for abbreviations, course numbers and coding.

DA2704Data Analytics using Python (Cross-listed: CS 2704) (A)4 ch (3C 1L) [P]
This course teaches data-driven problem solving. Starting from installing a Python programming environment, students will learn reading data, producing graphs, hypothesis testing and Bayesian statistics with hands-on programming experience. The course is also a stepping stone to more advanced subjects, such as machine learning and AI. Although no prior programming experience is required, there is a substantial programming component to the course.

Prerequisite: STAT 1793 or STAT 2593 or STAT 2263 or BA 1605 or PSYC 2901.
DA2714Text Analytics (Cross-listed: CS 2714) (O)3 ch (3C)
Introduction to the analysis of textual data with a foundation on natural language processing and computational linguistics. Students will learn to develop information extraction pipelines and evaluate performance.

Prerequisites: DA 2704, CS 1083, CS 1103
DA4403Data Mining (O) (Cross-Listed: CS4403)4 ch (3C 1L)

Data mining (aka knowledge discovery) is an interdisciplinary area of computer science with the goal of extracting new knowledge and insights from big and complex data sets. The course introduces essential pattern recognition methodologies leveraging machine learning and rule-based techniques. Supplementary tasks involving processing, cleaning, integration, and transformation of data are also covered. An etymology of data mining is provided to help students compare and contrast knowledge discovery with contemporary data analytics and decision support methodologies.

Prerequisites: CS 1103, CS 2704 and (STAT 2593 or STAT 2793).

DA4993Project in Data Analysis4 ch (2S) [W]

Application of correct and appropriate methods of data analysis in one or more areas. A project proposal is required with a final report in which the student describes clearly and concisely the work done, the results obtained, and a careful interpretation of the results in form and language meaningful to workers in the subject area. Students in the Certificate of Data Analysis should choose an industry-related or applied project involving a large amount of data. It should be noted that such a project may require extra time in order to become familiar with the data at hand. 

Prerequisite: Permission of Program Director.