MSc
Review the overview, fees, curriculum, instructors, and entry requirements in one place.
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.
The tuition amount above is shown with its payment cycle so applicants can understand how fees are charged for this program.
Application fee information is provided here to help prospective students review admission costs before beginning the application process.
For registration fees, totals, and full tuition tables, use the tuition page or contact admissions for the most current breakdown.
The first term strengthens statistical thinking, data programming, and applied modeling foundations.
Students build supervised and unsupervised learning capabilities while evaluating model fit, bias, and performance.
This stage covers data pipelines, warehousing concepts, visualization, and decision support infrastructure.
The final stage combines research, domain application, and presentation of a substantial data project.
Meet the instructors teaching this program.
Program Lead in Data Science
Teaches advanced analytics, machine learning, and decision intelligence for real-world data environments.
Applicants should hold a relevant undergraduate qualification and demonstrate readiness for advanced quantitative and computational study.
Students can review the fees, curriculum, and requirements here before starting the application.
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