The course
- Delivery
- Full-time, Part-time, Per course
- Course type
- Taught
- Location
- Edinburgh
- Entry date
- September
Contact
-
Contact
MACS PG Enquiries
-
Telephone
+44(0) 131 451 8444
Overview
Our Data Science masters teaches the theory and skills for managing and analysing large, complex data sets – sometimes called Big Data. You’ll learn how to model, store and process these data sets using the latest algorithms and techniques. Modern methods and tools for visually exploring the data will also be covered. The MSc course offers the key skill set of a data scientist. Optional courses provide an opportunity to explore closely-related areas based on the internationally leading research work of our academics.
The skills you learn through the Data Science masters will be applicable to industrial applications, as well as to scientific data exploration. In some cases, the MSc project can also be carried out in collaboration with an outside industrial or academic organisation
Course duration
- MSc: 12 months (full-time), 24 months (part-time)
- PG Diploma: 9 months
The full-time Masters in Data Science course starts in September.
Accreditation
The MSc is accredited by the British Computer Society.
Course content
Detailed course guideFull-time students take 4 courses each semester and must normally take all core courses.
Core Courses:
- Big Data Management
- Data Mining and Machine Learning
- Data Visualisation and Analytics
- Research Methods and Project Planning
- Masters project and dissertation
Optional Courses:
- Digital and Knowledge Economy
- Advanced Software Engineering
- Biologically Inspired Computation
- Computer Network Security
- Distributed and Parallel Technologies
- Information Systems Methodologies
- Software Engineering Foundations
- Conversational Agents and Spoken Language Processing
After semester 2 students continue full-time on the MSc project.
Further details are available here
Project
In the third semester (May-August) students undertake a specialist MSc project which is written up as a 15000 word dissertation. This project enables further development and consolidation of skills introduced in the taught courses, applying them to a challenging practical problem in this subject area.