Advanced Computer Science (Data Analytics)

Leeds University Business School

Postgraduate

In Leeds

Price on request

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Description

  • Type

    Postgraduate

  • Location

    Leeds

  • Start date

    Different dates available

Big data is becoming more and more important in fields from science to marketing, engineering medicine and government. This programme will equip you with specialist knowledge in this exciting field and allow you to explore a range of advanced topics in computer science.
You’ll gain a foundation in topics like systems programming and algorithms, as well as the basics of machine learning and knowledge representation. You’ll also choose from optional modules focusing on topics like image analysis or text analytics, or broaden your approach with topics like cloud computing.
As one of the few schools with expertise covering text, symbolic and scientific/numerical data analysis, we can provide a breadth of expertise to equip you with a variety of skills – and you’ll work as an integral member of one of our research groups when you develop your main project. We also have close links with the Leeds Institute for Data Analytics which is at the forefront of big data research.
Specialist facilities
You’ll benefit from world-class facilities to support your learning. State-of-the-art visualisation labs including a powerwall, a benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker are all among the specialist facilities we have within the School of Computing.
We also have Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices, Twin Immersion Corp CyberGloves, a cloud computing testbed, rendering cluster and labs containing both Microsoft and Linux platforms among others. It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology.

Facilities

Location

Start date

Leeds (North Yorkshire)
Maurice Keyworth Building, The University Of Leeds, LS2 9JT

Start date

Different dates availableEnrolment now open

About this course

Entry requirements
A bachelor degree with a 2:1 (hons) in computing or a related subject with a substantial computing element. Relevant work experience will also be considered.
We expect you to have programming competence, some prior experience of systems development and knowledge of data structures and algorithms.
All applicants will need to have GCSE English Language at grade C or above, or an appropriate English language qualification.
We accept a range of international equivalent qualifications.
English language requirements.
IELTS 6.5 overall, with no less than 6.0 in any component....

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This centre's achievements

2018

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More than 50 reviews in the last 12 months

This centre has featured on Emagister for 14 years

Subjects

  • Computing
  • Algorithms
  • Image
  • Project
  • Systems
  • Programming

Course programme

Core modules in Semester 1 will lay the foundations of the programme by giving you an understanding of the key topics of algorithms and systems programming, as well as the basic principles of automated reasoning, machine learning and how computers can be made to represent knowledge.

From there you’ll have the chance to tailor your studies to suit your own preferences. You’ll choose from a wide range of optional modules on diverse topics such as image analysis, cloud computing, semantic technologies and developing mobile apps.

Over the summer months you’ll also work on your research project. This gives you the chance to work as an integral part of one of our active research groups, focusing on a specialist topic in computer science and selecting the appropriate research methods.

Want to find out more about your modules?
Take a look at the Advanced Computer Science (Data Analytics) module descriptions for more detail on what you will study.

Course structure

These are typical modules/components studied and may change from time to time. Read more in our Terms and conditions.

Modules Year 1

Compulsory modules

  • Machine Learning 10 credits
  • Big Data Systems 15 credits
  • Data Science 15 credits
  • MSc Project 60 credits
Optional modules
  • Web Services and Web Data 10 credits
  • Distributed Systems 10 credits
  • Mobile Application Development 10 credits
  • Information Visualization 10 credits
  • User Adaptive Intelligent Systems 10 credits
  • Data Mining and Text Analytics 10 credits
  • Combinatorial Optimisation 10 credits
  • Secure Computing 10 credits
  • Graph Algorithms and Complexity Theory 10 credits
  • Bio-Inspired Computing 15 credits
  • Knowledge Representation and Reasoning 15 credits
  • Algorithms 15 credits
  • Parallel and Concurrent 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

For more information on typical modules, read Advanced Computer Science (Data Analytics) MSc in the course catalogue

Learning and teaching

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Advanced Computer Science (Data Analytics)

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