Undergraduate Certificate in Data Analytics

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)

DCS 400 Applied Statistics for Optimization 3 credit hours
DCS 401 Query Design and Analysis 3 credit hours
DCS 402 Big Data Analytics and Visualization 3 credit hours

DCS 403 Data Structures & Algorithms Design 

3 credit hours

DCS 404 Artificial Intelligence & Machine Learning  

3 credit hours
INT 301 Undergraduate Internship 1 credit hours