Undergraduate Certificate in Data Analytics

Program Description

Provides an overview of quantitative methods essential for analyzing data, with an emphasis on business applications. Topics include identification of appropriate metrics and measurement methods, descriptive and inferential statistics, experimental design, parametric and non-parametric tests, simulation, and linear and logistic regression, categorical data analysis, and select unsupervised learning techniques. Standard and open source statistical packages are used to apply techniques to real-world problems.

Program Learning Outcomes

1. Select, apply, and interpret appropriate statistical analyses and data mining methods for real-world data problems.
2. Apply knowledge and skills to real-world business challenges in advertising, sports, health, media and emerging technologies.
3. Detect algorithms and identify, categorize, and store data from multiple seemingly dissimilar sources
4. Analyze and model complex datasets and draws insights from the information available to solve problems for an organization or support its direction

Course Requirements (19 Credit Hours)