M.S. in Business Analytics

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The emergence of advanced technologies for capturing and analyzing data provides unprecedented opportunities for those with business analytics expertise that spans all industries and organizations. Combine your business skills and analytical acumen to become a professional with a Master of Science degree in Business Analytics (MSBA). By earning a master’s in business analytics, you will increase your viability in a competitive market for sought-after analytics professionals. Watch the MSBA Webinar.

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Program Features

The MSBA Program is offered in the Fall and Spring and is available both 100% online and in-person - no GRE/GMAT required!

THREE-FOCI STEM PROGRAM

The language of business today is dependent on information and data management. The Kent State University MSBA program provides you with a holistic knowledge of analytics that balances the technologies, analytical and business expertise you need to be able to glean useful information from data and make strategic business decisions.

With a KSU MSBA, you will gain the technical, analytical, communication, decision-making and leadership skills you need to be a successful business analyst. The in-person and online curriculum includes integrative capstone analysis projects, as well as an internship option for more professional development through our on-site Career Services Office dedicated to business students. With our STEM designation, international F-1 students qualify for OPT (Optional Practical Training), which helps them to acquire additional career experience while at Kent State.

Core Competencies

Data Mining / Machine Learning

Data Mining / Machine Learning

Principles of Machine Learning and Data Modeling

Data Structures and Types of Variables
Supervised vs. Unsupervised Machine Learning Modeling
Data Preparation Techniques
Feature Engineering
Evaluation of Machine Learning Models
Optimizing Machine Learning Models
Ensemble Learning
Common Mistakes in Modeling

Regression Modeling

Concepts and Definitions
Performance Metrics
Linear Regression
Generalized Linear Models (GLM)

Classification Modeling

Concepts and Definitions
Performance Metrics
Logistic Regression
k-Nearest Neighbor (k-NN)
Naïve Bayes
Decision Trees (applied to Regression as well)
Random Forrest (applied to Regression as well)
Gradient Boosted Machines (applied to Regression as well)
Support Vector Machines (applied to Regression as well)
Neural Networks (applied to Regression as well)

Recommendation Systems

Concepts and Definitions
Performance Metrics
Apriori algorithm for association data mining

Time Series Analysis

Concepts and Definitions
Performance Metrics
Stationarity, casuality and invertibility
Autoregressive Integrated Moving Average (ARIMA)

Graph Analytics

Concepts and Definitions
Centrality and Connectivity Measures
Application to Social Network Analysis

Text Analytics

Concepts and Definitions
Feature Extraction
Topic Modeling
Sentiments Analysis

Programming and Software Tools

Data Mining, Machine Learning and Quantitative Programming: R

Implementation of the following Data Mining/ Machine Learning methods:

Linear Regression
Generalized Linear Models
Logistic Regression
Decision Trees
Random Forrest
Gradient Boosted Machines
Support Vector Machines
Neural Networks

Implementation of the following Quantitative methods: R and Python

Linear Programming
Integer Programming
Goal Programming
Simulated Annealing
Network Models
Genetic Algorithms/ Programming

Data Preparation General Purpose Programming: R and Python

Calculating Various Statistics and Math Calculations
Calculating Probability Values
Data Input/ Export
Data Cleansing
Data Wrangling and Data Subsetting
Feature Engineering
Applying summarization and Aggregate functions

Database: SQL

Principals of Database Design
Using SQL to Create, Update and Delete Tables
Using SQL to Select a subset of Data
Using SQL to Join Tables
Using SQL to perform various Aggregate Functions

Visualization: R/Tableau/Microsoft Power BI

Using R ‘ggplot’ for explanatory analysis and communicating the insights
Using R ‘Shiny’ for interactive visualization and dash boarding
Using Tableau for explanatory analysis and communicating the insights

Software Repository and Development Platforms: Github/Git

Creating a new repository
Fork and Push changes to a repository
Clone a public project
Send a pull request/ Merge changes from a pull request

Curriculum Structure

Learn More

Admission

Admission occurs during the fall and spring and is highly competitive. Applying early is highly recommended as applications are reviewed on a rolling basis throughout the admission cycle. In addition to the online application form and fee, you must submit:

Accredited college/university official transcripts
Resume
Two letters of recommendation
Essay of goals and objectives
English score for international applicants (500 TOEFL paper-based, 79 TOEFL IBT, 6.5 IELTS, 110 Duolingo)
GMAT/GRE score is not required for this program

We look forward to seeing you in our master’s in business analytics program, so be sure your application materials fully meet the above requirements.

A MULTI-DISCIPLINARY GRADUATE PROGRAM

Due to its very multi-disciplinary nature, our MSBA accepts students with different academic backgrounds, including students with business, engineering, computer science, and other science disciplines. Some previous exposure to information/computer systems, applied statistics/math, and business, through coursework and/or work experience is expected.

Tuition and Financial Assistance

	Ohio Residents	Non-Ohio Residents
Below 11 credit hours	$549.90 per credit hour	$1,024.90 per credit hour
11-18 credit hours	$6,036	$11,261.40

Learn More | KSU Tuition & Fees

Scholarships:

Scholarships are available. These awards are very competitive and are awarded on the basis of academic merit

Faculty

The MSBA program at Kent State University is taught by full-time faculty with analytical and industry experience.

ROUZBEH RAZAVI, PH.D.

Director, MSBA Program

MURALI SHANKER, PH.D.

ALAN BRANDYBERRY, D.B.A.

CJ WU, PH.D.

Contact Us

LEARN MORE ABOUT OUR MSBA PROGRAM

If you would like to know more about our MS in business analytics, or want to get a better sense of what goes into our data analytics courses, be sure to reach out to us today.

Mason McLeod
Admissions Coordinator
mmcleod4@kent.edu