Data Science and Analytics
Postgraduate
In Leeds
Description
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Type
Postgraduate
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Location
Leeds
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Start date
Different dates available
We are surrounded by data. The variety and amount we collect and store grows every day, from the simplest of retail transactions to the complex and intimate medical records of millions.
Why do we store data? Where do we store it? How do we retrieve it? What do we use it for?
There is an increasing demand for individuals who can manage and control the way data is used. These individuals require an understanding of computer science and mathematics as well as a range of sector specific skills which can be applied in a variety of business environments.
The Data Science and Analytics MSc is a highly flexible course which offers the opportunity to develop a range of skills, including analysing structured and unstructured data, analysing large datasets and critically evaluating results in context, through a combination of compulsory and optional modules. By choosing appropriate modules you can follow specific pathways, in business management, healthcare or geographic information systems (GIS), which will allow you to tailor the programme to suit your background and needs.
The course combines expertise from the Schools of Computing, Geography and Mathematics with that of Leeds University Business School and the Yorkshire Centre for Health Informatics. This collaboration allows you to benefit from a range of data science perspectives and applications, supporting you to tailor your learning to your career ambitions.
Facilities
Location
Start date
Start date
About this course
Entry requirements
A 2:1 (hons) bachelor degree with a substantial numerate component. This may include degrees in mathematics, statistics, economics, engineering, or a physical science subject.
We accept a range of international equivalent qualifications.
English language requirements
IELTS 6.5 overall, with no less than 6.0 in all components. For other English qualifications, read English language equivalent qualifications.
How to apply
Application deadlines
31/07/18 - International
31/08/18 - Home/EU
APPLY riginal or certified copy of your IELTS/TOEFL results (if applicable)
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The average rating is higher than 3.7
More than 50 reviews in the last 12 months
This centre has featured on Emagister for 14 years
Subjects
- GCSE Mathematics
- GIS
- Business School
- Systems
- School
- University
- Mathematics
- Computing
- Retail
Course programme
The programme will equip students with the necessary knowledge and skills in data science.
Students on this programme will be benefit from being taught by experts from different academic units: the School of Mathematics; the School of Computing; the Yorkshire Centre for Health Informatics; the Faculty of Medicine and Health; the School of Geography and Leeds University Business School.
Modules are available from each of these areas. Mathematics modules are available for students who are not from a mathematics/statistics background, while Computing modules will be suitable for students on this programme who are not from a computer science background.
The programme will introduce you to different perspectives on data science, including the mathematical and computational underpinnings of the subject and its applications in specific contexts. You dissertation will enable you to span academic disciplines with supervision from both area. For this project you will interpret a real-world problem, coving data elucidation, analysis, and application.
Course structureThese are typical modules/components studied and may change from time to time. Read more in our Terms and conditions.
Modules Year 1Compulsory modules
- Data Science 15 credits
- Learning Skills through Case Studies 15 credits
- Dissertation in Data Science and Analytics 60 credits
- Distributed Systems 10 credits
- Machine Learning 10 credits
- Information Visualization 10 credits
- Big Data Systems 15 credits
- Data Management 15 credits
- Bio-Inspired Computing 15 credits
- Knowledge Representation and Reasoning 15 credits
- Systems Programming 15 credits
- Algorithms 15 credits
- Practical Programming 15 credits
- Data Mining and Text Analytics 15 credits
- Cloud Computing 15 credits
- Semantic Technologies and Applications 15 credits
- Image Analysis 15 credits
- Scheduling 15 credits
- Scientific Computation 15 credits
- Graph Theory: Structure and Algorithms 15 credits
- Geographic Data Visualisation & Analysis 15 credits
- Geodemographics and Neighbourhood Analysis 15 credits
- Big Data and Consumer Analytics 15 credits
- Predictive Analytics 15 credits
- Applied GIS and Retail Modelling 15 credits
Data Science and Analytics