MSc Data Science

Computer Science and Digital Technologies

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MSc

UCAS CODE

ENTRY REQUIREMENTS

Start Date(s)

Attendance

Learning

UCAS POINTS

UCAS points will be updated soon

September 2024

  • Full time, 1 year
  • Part time, 2 years
  • On campus
both CM2014
CM2014

Fees and Funding

Here's the fees and funding information for each year of this course

September 2024

Attendance

Fee

Note

Home
Full time, 1 year
£10,200
Per year
Part time
£1,700
Per year
International
Full time, 1 year
£15,960
Per year

Overview

WHAT YOU'LL LEARN

MODULES

  • Core Modules
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    Mental Wealth; Professional Life (Data Ecology)

    This module aims to develop a critical understanding of the world of data and Data Science from an ‘ecological’ perspective. This will focus on an understanding the environment of production, dissemination, harvesting and use of data in the data value chain as well as the development of niche areas from a perspective of evolution, competition, life cycle, cross-fertilisation and the niche space. This module focuses on many aspects of working in an Industry 4.0 economy.

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    Advanced Decision Making: Predictive Analytics & Machine Learning

    This module aims to develop a deep understanding of ways of making decisions that are based strongly on data and information. Particular focus will be on mathematical, statistical and algorithmic-based decision-making models using predictive analytics and machine learning. Various cases will be examined. The software environment will be predominantly open-source.

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    Spatial Data Analysis

    This module aims for students to understand the concept and theory of spatial data analysis, and develop the skill and problem-solving ability by applying a range of spatial query, processing, visualisation and analysis techniques. Main platforms with be open source SpatiaLite and QGIS.

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    Data Science Dissertation

    This module aims for students to conduct individual practical experience evaluation and academic research work around their own interest in the field of Data Science. Students are expected to demonstrate their ability of mastering the knowledge and skills acquired in taught modules. Students can negotiate with the team one of two alternative routes to completing a dissertation: either an evaluation of practical work experience (part 1, up to 50% of the mark as agreed with the teaching team) plus a related piece of academic research (part 2), or a single, extended, individual piece of academic research.

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    Variation for Online Learning Students

    This module aims for students to conduct individual practical experience evaluation and academic research work around their own interest in the field of Data Science. Students are expected to demonstrate their ability of mastering the knowledge and skills acquired in taught modules. Students complete a single, extended, individual piece of academic research.

HOW YOU'LL LEARN

HOW YOU'LL BE ASSESSED

CAMPUS and FACILITIES

Docklands Campus

Docklands Campus, Docklands Campus, London, E16 2RD

WHO TEACHES THIS COURSE

The teaching team includes qualified academics, practitioners and industry experts as guest speakers. Full details of the academics will be provided in the student handbook and module guides.

YOUR FUTURE CAREER