Master of Business Analytics

Program Overview

The Master of Business Analytics program equips students with the skills to thrive in a data-driven world. The program focuses on data analysis, problem-solving, visual and computational analytics, and data-driven investigations. Graduates are prepared for careers in data analytics and other fields that rely on data-driven decision-making. The program is taught by experienced faculty and incorporates the latest research and industry best practices.

Program Outline

Degree Overview:

Overview:

The Master of Business Analytics program equips students to thrive in a data-driven world by developing the data analysis and problem-solving skills they need to solve real-world challenges. The program focuses on the nature of data, including Big and Unstructured Data, and teaches students how to embark on data-driven investigations and utilize visual and computational analytics. Upon completion of the program, graduates will be prepared to excel in a range of industries and sectors that rely on data analytics.

Objectives:

• Understand the nature of data, including Big and Unstructured Data.
• Develop proficiency in data analysis and problem-solving skills.
• Acquire expertise in visual and computational analytics.
• Gain the knowledge and skills necessary to embark on data-driven investigations.
• Prepare for careers in data analytics and other fields that rely on data-driven decision-making.

Outline:

Program Content:

The program covers a broad range of topics in business analytics, including:

• Data management and data mining
• Data visualization and communication
• Predictive modeling and forecasting
• Machine learning and artificial intelligence
• Business intelligence and data warehousing
• Cloud computing and big data technologies

Program Structure:

The program consists of 80 credit points of coursework. Students can complete the program full-time in two years or part-time in three years. The program is offered on a trimester system, with classes typically meeting once or twice per week.

Individual Modules:

Data Management and Data Mining

• Introduction to data management and data mining concepts and principles.
• Hands-on experience with data management and data mining tools and techniques.
• Applications of data management and data mining in real-world business settings.

Data Visualization and Communication

• Fundamentals of data visualization and its role in business decision-making.
• Hands-on experience with data visualization tools and techniques.
• Practical applications of data visualization in various business contexts.

Predictive Modeling and Forecasting

• Introduction to predictive modeling and forecasting concepts and methods.
• Hands-on experience with predictive modeling and forecasting tools and techniques.
• Applications of predictive modeling and forecasting in various business contexts.

Machine Learning and Artificial Intelligence

• Overview of machine learning and artificial intelligence concepts and algorithms.
• Hands-on experience with machine learning and artificial intelligence tools and techniques.
• Applications of machine learning and artificial intelligence in various business contexts.

5. Business Intelligence and Data Warehousing

• Understanding of business intelligence and data warehousing concepts and technologies.
• Hands-on experience with business intelligence and data warehousing tools and techniques.
• Applications of business intelligence and data warehousing in various business contexts.

Cloud Computing and Big Data Technologies

• Exploration of cloud computing and big data technologies and their applications in business.
• Hands-on experience with cloud computing and big data technologies.
• Analysis of case studies and examples of cloud computing and big data technologies in practice.

Assessment:

Assessment in the Master of Business Analytics program is based on a combination of coursework and examinations. Coursework may include assignments, projects, presentations, and case studies. Examinations may be in the form of written exams, oral exams, or take-home exams. Grading is based on a 4-point scale:

• High Distinction (HD)
• Distinction (D)
• Credit (C)
• Pass (P)
• Fail (F)
To pass the program, students must achieve a passing grade in all courses. Students who achieve a high overall average may be awarded a High Distinction (HD) or Distinction (D).

Teaching:

The Master of Business Analytics program is taught by a team of experienced faculty members who are active researchers in the field of data analytics. Faculty members use a variety of teaching methods, including lectures, discussions, case studies, and hands-on exercises. The program also incorporates the latest research and industry best practices into the curriculum. Students have the opportunity to work on real-world data analytics projects and interact with industry professionals.

Careers:

Graduates of the Master of Business Analytics program are in high demand in a wide range of industries, including:

• Finance and banking
• Healthcare
• Manufacturing
• Retail
• Technology
Common job titles for graduates include:
• Analytics manager
• Analysis director
• Insights and data manager
• Data scientist
• Business analyst