Data Analytics Minor (19 hours)
CMPSC 2200 Python Programming I (4 hours)
An introduction to computational problem-solving using Python. Hands-on labs are used to motivate basic programming concepts, including basic data types and structures, functions, conditionals, and loops. Additional topics may include building and scraping HTML webpages. The course is recommended for all who wish to explore data science and/or computer science. Recommended: Math ACT score of at least 21 or instructor permission of a prerequisite waiver.
(Normally offered every spring semester.)
Archway Curriculum: Foundational Literacies: Mathematical Problem Solving
DATA 1200 Excel and SQL Programming (4 hours)
A study of managing, manipulating, and summarizing data using Excel and SQL. Topics in Excel include, but are not limited to: functions, filters, charts and visualizations, pivot tables, and macros. Topics in SQL include, but are not limited to: queries, joins, and basic database management.
(Normally offered every spring semester.)
Archway Curriculum: Foundational Literacies: Mathematical Problem Solving
DATA 1350 Introduction To Data Analytics (4 hours)
An introduction to data analytics from three perspectives: inferential thinking, computational thinking and real-world relevance. Topics include, but are not limited to: organizing real-world data by filtering, sorting, and using pivot tables; exploring data; visualizing data; using programming tools to analyze data through a statistical lens. Statistical topics include: center and spread of data, descriptive statistics, inferential statistics, regression, causality, classification and prediction.
(Normally offered every fall semester.)
Archway Curriculum: Foundational Literacies: Mathematical Problem Solving
DATA 3100 Data Visualization With R (4 hours)
A study of data visualization, including principles and techniques. Students will analyze the effectiveness of visualizations, create a wide array of visualizations using the programming language R, and communicate a story through them. Significant emphasis will be placed on getting and cleaning data.
Prerequisite(s): Grade of "C" or better in CMPSC 2200 Python Programming I and grade of "C" or better in MATH 1300 Statistics.
(Normally offered every spring semester.)
MATH 1300 Statistics (3 hours)
An introduction to statistics concepts with an emphasis on applications. Topics include descriptive statistics, discrete and continuous probability distributions, the central limit theorem, confidence intervals, hypothesis testing, and linear regression.
(Normally offered every semester.)
Archway Curriculum: Foundational Literacies: Mathematical Problem Solving