MASTER IN DATA SCIENCE - PART TIME (ODL) at Sunway University

Program Structure: Developing Expertise in Data Science

The programme consists of core subjects, electives, and a capstone research project. It is structured to build knowledge progressively from fundamental techniques to advanced data science applications. :contentReference[oaicite:2]{index=2}

• Core Subjects
  • Principles & Practices of Data Science
  • Programming for Data Science
  • Data Visualisation
  • Statistical Methods for Data Science
  • Data Mining
  • Big Data Management
  • Research Methodology
• Electives (Choose Several)
  • Forecasting Analytics
  • Deep Learning for Data Science
  • Cloud Infrastructure & Services
  • Social & Digital Media Analytics
  • Artificial Intelligence
  • Data Science Ethics
• Capstone Project
  • Applied Data Science Project (two parts)
  • Project Report & Presentation

Entry Requirements

• Academic Qualifications: Bachelor’s degree in computing, IT, mathematics, statistics, business, or related fields with a satisfactory CGPA (often around 2.50 or equivalent). :contentReference[oaicite:3]{index=3}
• Prerequisite Pathway: Applicants from non-computing backgrounds may take prerequisite units in programming and database concepts before starting the Master’s. :contentReference[oaicite:4]{index=4}
• English Language Requirements: IELTS 6.0 or equivalent is commonly required if prior education was not in English. :contentReference[oaicite:5]{index=5}

Career Opportunities

Graduates of this part-time online Master in Data Science are prepared for professional roles where data expertise is crucial. They develop skills to interpret data, build models, and contribute to strategic decisions across sectors. :contentReference[oaicite:6]{index=6}

• Data Scientist
• Data Analyst
• Big Data Specialist
• Machine Learning Engineer
• Business Intelligence Analyst
• Analytics Consultant
• AI & Predictive Analytics Specialist

Program Highlights

• Duration: Typically 2 years part-time (online). :contentReference[oaicite:7]{index=7}
• Mode of Delivery: Fully online via ODL, with no requirement to attend campus. :contentReference[oaicite:8]{index=8}
• Flexible Scheduling: Multiple entry points throughout the year and self-paced study. :contentReference[oaicite:9]{index=9}
• Capstone Focus: Applied project enables real-world problem solving with data. :contentReference[oaicite:10]{index=10}
• Industry Relevance: Curriculum aligned with employer demand for data-driven expertise. :contentReference[oaicite:11]{index=11}
• Global Opportunities: Robust data science education for careers worldwide. :contentReference[oaicite:12]{index=12}
• Prerequisite Support: Bridging units available for students without computing backgrounds. :contentReference[oaicite:13]{index=13}