MSA (Business Analytics)

This course provides an introduction to online learning and the necessary knowledge and skills required to complete courses in the blackboard e-learning environment.

Provides an overview of the business analytics process and important analytic techniques; data visualization, data mining, optimization, and simulation. Exposes students to a variety of business problems in analytics (marketing, finance, operations). Throughout the course, students will learn to model and analyze complex business decisions with various tools on spreadsheets to improve decision making across business functions.

The fundamentals of the usage of R and Python as programming languages, with emphasis on applications in business. Students will learn fundamentals of both languages and will be exposed to cutting edge packages and libraries to execute analytic tasks.

Covers the concepts and techniques used to analyze and report structured data. Students will learn tools and methods for understanding the data models supporting various business processes and for analyzing data from structured databases.

Multivariate Data Analysis focuses on skills students need to analyze and interpret data sets. Students will learn to analyze data and interpret results using a variety of methods including data visualizations, multiple linear regression, variance models analysis, and Chi-square models.

This course is a 1 time course for 1 specific study.

The objective of this course is teaching students how to use various mining data techniques. Topics include logistic regression, decision tree networks, and neural networks. Student will mine datasets from various business areas and use their findings to support decision-making.

This course focuses on text and web mining and their applications. Roughly 80% of data is unstructured. However, it is difficult to work with unstructured data. This course covers techniques for mining text and web data to improve business decision making. Topics include text/web retrieval, classification/clustering, transforming text data into a structured format, text summarization, and social network analysis. Students will also be exposed to big data issues and interact with web APIs from popular web sites for data collection.

This course examines the concepts and approaches in Business Intelligence (BI) from a business user/analyst perspective. Students will learn to use BI tools for creating applications and dashboards in the context of fact-based decision-making.

This course builds on the material from earlier courses in the program. It provides students with a chance to dive deeper into critical optimization, probability, and simulation modeling techniques useful in today's business environment. This course begins with a review of modeling basics, expands the student's exposure to optimization modeling techniques for both linear and non-linear problems, and introduces simulation modeling using an industry-leading simulation software package. Students are exposed to a variety of business problems in analytics (marketing, finance, operations). Throughout the course, students will learn to model and analyze complex business decisions with various tools to improve decision-making across business functions.

This course covers the use of machine learning algorithms in business decision making and the potential drawbacks and ethical challenges. A particular focus will be on preprocessing, coding and evaluation methodologies for deep learning.

This course introduces how data warehouses provide the foundation for analytics within enterprises. Students learn the dimensional model, how data warehouses and data marts are designed and created, including the ETL process, where data is cleaned and structured for analysis

This course focuses on advanced applications in business. Case discussion will be used to expose students to diverse applications of analytics in organizations. Assignments include case discussion, problem solving, projects to further students' knowledge and skills.

In this capstone course, students will implement concepts and skills learned throughout the program to navigate the process of working with an organization on a business project. Lectures and assignments will help students obtain skills needed to support their client