Data Science (with specialisation in Visualization) MSc, PGDip, PGCert
Program start date | Application deadline |
2023-09-01 | - |
Program Overview
Overview
Data Visualisation is an increasingly important part of data science. It aims to bridge the gap between the human and data. It supports human perception and cognition to make sense of data analytics outputs.
We created the PGDip, PGCert, MSc Data Science with Specialisation in Visualisation in collaboration with a number of high profile industry leaders. It aims to address the skills shortage in data analytics.
Our master's in data science brings together students and industry practitioners to develop and translate new technologies into industry practice.
You'll receive a comprehensive grounding in the theory and application of data science. You'll also gain the ability to apply these skills to real problems in a given application area.
Through project work, you'll experience the full lifecycle from design of interactive visualization to experimental evaluation of an advanced visualization approach.
Topics covered in the course include:
You'll benefit from our substantial expertise in data science. We focus on a wide range of application areas, including:
This data science course is part of the following suite:
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Important information
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Program Outline
What you'll learn
The MSc data science has three phases.
In phase one you’ll be introduced to core knowledge and skills in statistics and computer science.
These modules are taught as an intensive block, with two modules taught concurrently for full-time students. Teaching is timetabled to accommodate participants from industry, working alongside full-time employment.
Phase two will present further advanced technical modules. You'll be introduced to the aspects that underlie all areas of data science practice including:
This phase also includes a group project in collaboration with industry. You'll develop and evaluate a data science solution to a complex, real-world problem.
Phase three is an individual research and development project. You'll receive personal supervision in one of the School’s research labs in collaboration with industry or with your current employer.
This MSc forms part of the following suite of data science courses:
Modules
You will study modules on this course. A module is a unit of a course with its own approved aims and outcomes and assessment methods.
Course content changes
Module information is intended to provide an example of what you will study.
Our teaching is informed by research. Course content changes periodically to reflect developments in the discipline, the requirements of external bodies and partners, and student feedback.
Full details of the modules on offer will be published through the Programme Regulations and Specifications ahead of each academic year. This usually happens in May.
Optional modules availability
Some courses have optional modules. Student demand for optional modules may affect availability.
To find out more please see our terms and conditions.
Data Science (Visualization) MSc modules
Compulsory Modules | Credits |
---|---|
Engineering for AI | 10 |
Data Visualization | 10 |
Data Management and Exploratory Data Analysis | 10 |
Data Science in the Wild | 10 |
Group Project in Data Science | 10 |
Machine Learning with Project | 10 |
Complex Data Visualization | 10 |
Project and Dissertation in Data Science | 80 |
Statistical Foundations of Data Science | 10 |
Statistical Learning for Data Science | 10 |
If you have permission from the Degree Programme Director, you can swap Engineering for AI to take one elective module from the following list:
Optional Modules | Credits |
---|---|
Image Informatics | 10 |
Cloud Computing with Project | 10 |
Data Science (Visualization) PGDip modules
Compulsory Modules | Credits |
---|---|
Engineering for AI | 10 |
Data Visualization | 10 |
Data Management and Exploratory Data Analysis | 10 |
Data Science in the Wild | 10 |
Group Project in Data Science | 10 |
Machine Learning with Project | 10 |
Complex Data Visualization | 10 |
Diploma Project and Dissertation in Data Science | 20 |
Statistical Foundations of Data Science | 10 |
Statistical Learning for Data Science | 10 |
If you have permission from the Degree Programme Director, you can swap Engineering for AI to take one elective module from the following list:
Optional Modules | Credits |
---|---|
Image Informatics | 10 |
Cloud Computing with Project | 10 |
Data Science (Visualization) PGCert modules
Optional Modules | Credits |
---|---|
Engineering for AI | 10 |
Data Visualization | 10 |
Image Informatics | 10 |
Data Management and Exploratory Data Analysis | 10 |
Data Science in the Wild | 10 |
Group Project in Data Science | 10 |
Cloud Computing with Project | 10 |
Machine Learning with Project | 10 |
Complex Data Visualization | 10 |
Statistical Foundations of Data Science | 10 |
Statistical Learning for Data Science | 10 |
If you have permission from the Degree Programme Director, you can swap Engineering for AI to take one elective module from the following list: