5 courses with the subject APAN, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
APAN 6010Computer Aided Multivariate Analysis3
The course was designed to continue statistical application for big data analysis. The analysis of big data provides a challenge for how to best analyze large amounts of data that will aid in decision making. This course will look at how to use regression analysis to test hypothesis and how to select the best type of regression analysis for the decision maker.
This course prepares students to analyze structured data using Microsoft Power BI and Excel. Students will apply data modeling, time series forecasting, segmentation, and simulation-based decision-making techniques to solve real-world business problems. Emphasis is placed on using visualization and storytelling tools to communicate insights and support strategic decisions. Course Materials: The software required for this course is Microsoft PowerBI.
Data mining is the practice of automatically searching large stores of data to discover patterns and trends that go beyond simple analysis. Data mining uses sophisticated mathematical algorithms to segment the data and evaluate the probability of future events. The fundamental algorithms in data mining and analysis are the basis for business intelligence and analytics as well as automated methods to analyze patterns and models for all kinds of data. Data mining is also known as Knowledge Discovery in Data (KDD). The course is designed to provide the business or IT professional with a practical working knowledge of data mining algorithms, concepts, and best practices. Students will use technology to work on real-life data mining tasks, mastering features of technology.
The course was designed as an experiential component centered around at least one capstone project, potentially developed with an employer, supervised collaboratively by faculty, and evaluated by faculty. This capstone practicum integrates the practical application of data analytics and professional knowledge to lead to sound management decisions based on big data analysis. The experiential component may include a structured internship either at the student’s current place of employment or a self-directed project based on the selected track of the degree. The final project will include both an oral and written report on the findings and recommendations from a collection of data, analyzed using any contemporary analytics tools & methods. Prerequisites: APAN 6010, APAN 6015, INFT 6015.
