Master in Business Analytics
The post-graduate program in Business Analytics at UAEU introduces the various information technologies, as well as analytical models and methods, for transforming business data into information, knowledge, and subsequently digital assets. The program provides the fundamental background, as well as advanced applications of statistics, visual analytics, machine learning, data analytics, optimization, and other analytical techniques. Three distinctive features of the program are: the emphasis on real-world applications in diverse functional areas of business; the enrichment of lecture materials through practical experience with state-of-the-art software tools; and the flexible program structure which allows for conducting a capstone project based on a data-driven real world problem coming from a client company.
Each course is delivered in an intensive mode during an eight weeks term through 9 sessions of 5 hours each. The Fall and Spring semesters consist of two eight weeks terms each. Two courses are offered each term.
Program Objectives
- Knowledge and skills in analytical modeling and problem solving.
- Critical thinking, research, and analytical skills to gather data and information and solve problems involving big and/or complex data.
- Effective work and communication skills, including the ability to work efficiently and effectively in teams.
- Skills to execute ethical standards and comply with laws in organizations, at local and global levels.
Program Learning Outcomes
Upon successful completion of this program, students will be able to:
- Appraise various information technologies, as well as analytical models and methods, through advanced and specialized knowledge, for transforming data into information, knowledge, and subsequently digital assets.
- Select descriptive, diagnostic, predictive, and prescriptive analytical models, methods, and tools, based on problem context, business objectives, and data sources.
- Apply analytical methods, including statistics, data analytics, and optimization, for advanced analysis of data-driven problems in business and industry.
- Develop innovative research-driven solutions for discovering actionable insights, driving sustainable decisions, and developing novel business models.
- Communicate effectively to specialized and non-specialized audiences, verbally, visually, and in writing, the results and interpretation of data-centric analyses of business and industry problems.
- Execute business analytics activities and projects with autonomy, entrepreneurship, and leadership.
- Conduct business analytics activities and projects as an effective and collaborative team member.
- Implement the principles of privacy, ethics and governance in business analytics, while reflecting on socio-cultural norms.
Degree Requirements
Required Credit Hours : minimum 30 hours
Core Requirements
Required Courses (18 hours ) | Credit Hours | |
---|---|---|
BANA520 | Digital Business Innovation | 3 |
BANA540 | Visual Analytics & Business Intelligence | 3 |
BANA560 | Applied Optimization | 3 |
BANA600 | Business Analytics Applications | 3 |
STAT520 | Foundations for Analytics | 3 |
STAT555 | Data Analytics & Machine Learning | 3 |
Projects/Capstones (Required Credit Hours: 3 - 6)
Students should take either BANA 690 or, BANA 691 and BANA 692 (6 hours ) | Credit Hours | |
---|---|---|
BANA690 | Analytics Project | 3 |
BANA691 | Capstone Project I | 3 |
BANA692 | Capstone Project II | 3 |
Elective Courses ( 6 CR or 9 CR)
1 - Students who take the Analytics Project (BANA 690) should select 9 credit hours from the courses listed below. 2 - Students who take the Capstone Project (BANA 691 and BANA 692) should select 6 credit hours from the courses listed below. (9 hours ) | Credit Hours | |
---|---|---|
BANA652 | Analytics for Accounting & Finance | 3 |
BANA655 | People Analytics | 3 |
BANA661 | Marketing Analytics | 3 |
BANA656 | Analytics for Operations & Supply Chains | 3 |
Bridging Course
This bridging course is only needed for students who did not take an undergraduate statistics course and is a prerequisite for the STAT 520 - Foundations for Analytics (0 hours ) | Credit Hours | |
---|---|---|
STAT501 | Statistics Bridging (online-MBAN) | 0 |
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