Master of Business Data Science

Program Overview

The Master of Business Data Science program equips students with the skills to analyze strategic data in business contexts. Through a diverse curriculum covering coding, data analytics, machine learning, and data science, students develop advanced analytical skills for enhanced decision-making and prepare for careers in data-driven business environments.

Program Outline

Degree Overview:

Master of Business Data Science

Overview:

The Master of Business Data Science program is designed to equip students with the skills and knowledge necessary to delve into strategic data analytical aspects of business and its growth. The program prepares students for key analytical skills crucial in today's digital environment, such as business analytics, data analytics, machine learning engineering, and data science. Real-world business problems are leveraged within the program to engage in practical applications.

Objectives:

• Produce professionals with the skillset to analyze strategic data in business contexts.
• Develop key analytical skills for a digital environment.
• Emphasize advanced data analytical skills for enhanced decision-making.
• Fulfill the increasing demand for data analysts, business analysts, machine learning engineers, and data scientists in the Malaysian economic scenario.

Description:

The program leverages a diverse set of modules to prepare students for careers in data-driven business environments. The curriculum covers:

• Coding for Data Science
• Business Data Techniques & Analytics
• Research Methods for Business Data Science
• Data Management
• Applied Machine Learning
• Behavioral Science for Business Domain
• Data Mining and Statistical Methods
• Research Project 1
• Cloud Infrastructure and Services
• Data Storytelling and Analytics
• Natural Language Processing
• Research Project 2
Each module is designed to provide students with comprehensive knowledge and practical application opportunities. Through this rigorous curriculum, students gain the ability to:
• Communicate data-driven solutions effectively

Outline:

Semester 1:

• Coding for Data Science:
Introduces students to programming languages and tools relevant for data analysis.
• Business Data Techniques & Analytics:
Covers foundational concepts of business data analysis, including data collection, cleaning, and visualization.
• Research Methods for Business Data Science:
Equips students with research design skills applicable to data-driven business contexts.
• Data Management:
Explores database systems, data warehousing, and data governance strategies.

Semester 2:

• Applied Machine Learning:
Teaches various machine learning algorithms and their applications in business decision-making.
• Behavioral Science for Business Domain:
Explores how understanding human behavior can influence data-driven decision-making strategies.
• Data Mining and Statistical Methods:
Delves into advanced data mining techniques and statistical methods for uncovering hidden patterns in data.
• Research Project 1:
Provides the opportunity to apply learned skills by conducting an initial research project focused on analyzing a chosen business domain.
• Natural Language Processing:
Introduces students to NLP concepts and algorithms for processing textual data in business applications.
• Research Project 2:
Enables students to further hone their research skills by applying them to a more substantial project with real-world relevance.

Assessment:

Assessment strategies for the Master of Business Data Science might include:

• Written assignments:
Essays, reports, and case studies requiring analysis and interpretation of data from various business contexts.