Master of Data Science
The Master of Data Science is built for professionals and advanced graduates who want strong capability in analytics, machine learning, and data-driven decision systems.Students study statistical modeling, machine learning, data e...
Program overview
The Master of Data Science is built for professionals and advanced graduates who want strong capability in analytics, machine learning, and data-driven decision systems.
Students study statistical modeling, machine learning, data engineering, visualization, and responsible AI while completing applied projects that reflect current institutional and industry data challenges.
Expected outcomes
Key activities
Program components
Core Analytical Foundations
The first term strengthens statistical thinking, data programming, and applied modeling foundations.
- Advanced statistics and inference
- Programming for analytics workflows
- Structured analytical reasoning
Machine Learning and Predictive Systems
Students build supervised and unsupervised learning capabilities while evaluating model fit, bias, and performance.
- Machine learning methods
- Model evaluation and validation
- Applied predictive problem solving
Data Engineering and Decision Platforms
This stage covers data pipelines, warehousing concepts, visualization, and decision support infrastructure.
- Data engineering and pipeline design
- Visualization and storytelling
- Analytics products and dashboards
Applied Research and Capstone
The final stage combines research, domain application, and presentation of a substantial data project.
- Research methods for data science
- Applied capstone or dissertation
- Professional presentation and impact reporting
Participation guidance
Applicants should hold a relevant undergraduate qualification and demonstrate readiness for advanced quantitative and computational study.
- Relevant bachelor degree in computing, mathematics, engineering, or a related field
- Evidence of analytical and quantitative readiness
- Professional experience with data is an advantage but not mandatory
Need more information?
Contact SOEYDA for partnership, implementation, or field coordination details.