This course explores key principles and techniques of data science in Python, including programming foundations, data management, advanced data visualization, integration with SQL, and machine learning. The class has optional live sessions.
Prerequisite(s): CMPSC 3200 Python Programming II and DATA 1350 Introduction To Data Analytics.
This course is offered online through a consortium of accredited colleges and universities. Instruction is provided by faculty employed by partner institutions within the consortium, with technology and administrative support provided by Rize Education. Oversight of courses offered through the consortium are reviewed and approved by Nebraska Wesleyan University. Students register through Nebraska Wesleyan University and receive academic credit from Nebraska Wesleyan University.
CMPSC 3200 Python Programming II (4 hours)
A project-based continuation of the techniques developed in CMPSC 2200 Python Programming I. Topics include object-oriented programming, algorithm design and analysis, data structures, and general problem-solving techniques (such as recursion) while following industry-standard software development principles. Prerequisite(s): Grade of "C" or better in CMPSC-2200 or instructor permission of a prerequisite waiver.
(Normally offered every fall semester.)
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