MSBA Program Design

The Milgard School of Business MSBA degree integrates STEM (Science, Technology, Engineering, Mathematics) perspective into business education and analysis.

Milgard's MSBA is a diligently designed hybrid, 9 month, work-compatible masters degree. MSBA delivers the ultimate curriculum that will develop the next generation of analytics savvy business analysts, project managers, analytics managers, chief analytics officers, digital talents, and T-shape analytical thinkers and adaptive innovators.

Curriculum

The Milgard School of Business MSBA degree is 40 credits of graduate courses over the course of 9 months.

 

AUTUMN

WINTER

SPRING

Business

Data

Analytics

Information

Analytics Strategy & Big Data Management

Business Process & Workflow Analysis

Analytical Decision Making

Applied Regression Models

Data Mining

 

Text Mining

Business Analytics

Social Media Analytics

Knowledge

Wisdom

Practice

Outcome

Applied Project: Digital Transformation Lab I

 

Applied Project: Digital Transformation Lab II

Applied Project: Digital Transformation Lab IV

Applied Project: Digital Transformation Lab III

 

 

Summary of Courses

Business, Data, Analytics, and Information Courses

Course Number

Course Title

Credits

TMSBA 510

Business Analytics

Focuses on foundations of evidence based management. Explains the concepts with innovative uses of information systems, data, information, knowledge and analytics to support managerial decision-making. Explores how to collect, store, manage and convert data to information, knowledge and actionable insights.

4

TMSBA 520

Analytics Strategy and Big Data Management

Gartner Research indicates that more than 50% of Business Analytics (BA) projects fail due to not following fundamental project management principles. Focuses on how organizations need to make analytics part of their organizational strategy, and how they can implement analytics projects successfully by following sound project management principles. It focuses on strategy definition, initiating, planning, executing, controlling and completing analytics projects in a variety of environments for sustainable competitive advantage.

4

TMSBA 530

Business Process and Workflow Analysis

Focuses on how organizations can evaluate, design and implement sound business process management practices, and integrate analytics into their business processes and workflows for maximum performance. The course will also cover Service Oriented Solutions (e.g. dynamic business processes, architectures and infrastructures), data and predictive model ownership issues, embedding analytics in business processes, alignment of business process management with corporate strategy.

4

TMSBA 540

Applied Regression Models

Focuses on statistical foundations of decision making processes. Topics will include, but are not limited to:  multiple linear regression, models for quantitative and qualitative predictors, building regression models, autocorrelation, non-linear regression, piecewise linear regression, inverse prediction, weighted least squares, ridge regression, robust regression and non-parametric regression.

4

TMSBA 550

Analytical Decision Making

Focuses on the skills and knowledge necessary for mastery of the use of quantitative modeling tools and techniques to support decision analysis. Some of the deterministic optimization techniques (e.g. linear, nonlinear, integer optimization, network models) and uncertain decision making techniques (e.g. decision trees, transportation models, queuing theory) are covered.

4

TMSBA 560

Data Mining

Focuses on some of the primary business data mining topics (descriptive, predictive and prescriptive) through advance analysis of applied, realistic datasets in areas like demand forecasting, credit scoring, customer relationship management, financial analysis, healthcare and supply chain management.

4

TMSBA 570

Text Mining

This course will cover the basic concepts, principles, and major algorithms in text mining. These will be used to discover interesting patterns, extract useful knowledge, and support decision making.

4

TMSBA 580

Social Media Analytics (will be offered during AY 2017-18)

Focuses on some of the primary concepts, methods, tools and solutions to develop a social media strategy, and to collect, process and transform social media data into information processes, knowledge, actionable decisions and processes. It also covers how organizations make use of social media as a strategy to gain a competitive advantage.

4

 

OR

 

TMSBA 585

Cognitive Analytics (will not be offered during AY 2017-18)

Evaluate the concepts with innovative uses of cognitive solutions to either solve existing business problems or create new business opportunities, and improve the performance of organizations. Analyze how to utilize cognitive tools, assistants, collaborators and coaches effectively.

4

 

Total Credits

32

 

Knowledge, Wisdom, Practice, and Outcome Courses

TMSBA 591

Applied Project: Digital Transformation Lab I

Focuses on how to apply the concepts, methods and solutions associated with data, analytics, smart machines and digital solutions to real opportunities in an application domain. Topics will include, but are not limited to: analysis of organization and market demand, business model development, opportunity analysis for digital transformation.

2

TMSBA 592

Applied Project: Digital Transformation Lab II

Focuses on processes performed to analyze and plan digital transformation and innovation to a wide variety of opportunities and challenges. Topics will include, but are not limited to: requirements gartering, defining scope, risk analysis, detailed transformation and technology planning.

2

TMSBA 593

Applied Project: Digital Transformation Lab III

Focuses on processes performed to design and develop data and digital solutions to a wide variety of opportunities and challenges. Topics will include, but are not limited to: collection, storage, analysis of data and development of digital solutions.

2

TMSBA 594

Applied Project: Digital Transformation Lab IV

Focuses on processes performed to prototype data and digital solutions to a wide variety of opportunities and challenges. Topics will include, but are not limited to: develop, prototype and lessons learned, analyze findings, recognize ethical dilemmas and social responsibilities.

2

 

Total Credits

8

Back to top