M.Sc. Data Systems

The M.Sc. Data Systems trains students to design, build, and govern the systems that store and analyze data at scale, with a strong thread of privacy and ethics running through every course.

Learning Outcomes

Design large-scale data storage and processing systems.
Apply machine learning methods responsibly to real datasets.
Evaluate the privacy and governance implications of a data system.
Complete an applied data systems project with a partner organization.

Curriculum Structure

400 Level

CSC403 CSC404

Related Courses

Core200 Level

CSC204

Database Systems I

Database Systems I covers relational database design, query languages, and the principles that keep data consistent and retrievable at scale. Students design a schema from a real-world scenario, populate it, and write queries that answer genuine questions about the data.

Priya Raghunathan 3 cr

Core300 Level

CSC304

Machine Learning

Machine Learning covers the core supervised and unsupervised learning methods, how to evaluate them honestly, and where they tend to fail. Every technique is paired with a discussion of its assumptions, so students learn to ask what a model actually knows, not just what it outputs.

Sofia Reyes 4 cr

Elective400 Level

CSC403

Cloud Computing & Systems at Scale

Cloud Computing & Systems at Scale examines how modern applications are deployed, scaled, and kept resilient across managed infrastructure. Students design and deploy a small application under simulated load, then diagnose and fix the bottlenecks that appear.

Daniel Osei 3 cr

Admission Overview

Admission requires an undergraduate degree with demonstrated coursework in databases or statistics, transcripts, and a statement of interest.

Entry Level

B.Sc. in Computer Science, Data Science, or a closely related field.

Career Directions

Data EngineerData Systems ArchitectAnalytics EngineerResearch Data Scientist