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  • DeadlineStudy Details: 1 year full-time (September start) and 16 months full-time (January start)

Masters Degree Description

Overview

Master big data methodologies and find the valuable trends and patterns buried in complex datasets using machine learning. On our MSc Data Analytics course, you'll learn how to use data mining tools, machine learning methods and big data concepts as you unlock specialist knowledge of professional analysis methods.

You'll apply your theoretical learning to handling real data, analysing large data sets drawn from professional partners, such as IBM, or from live University research into cosmology, health informatics and cybersecurity and robotics. 

You'll plan, design and produce an in-depth research project, using analytics packages like Hadoop, Python, KNIME, PostgreSQL and Tableau. We'll provide the expertise and support so you can develop your dissertation and shape your professional practice. And once you graduate, you'll have a skillset that'll get you noticed – and all the tools you need to progress your career in data analytics or deep learning.

Course highlights

  • Plan and deliver your Master's project in collaboration with an industry partner – previous projects have analysed data from Fresh Relevance, Specsavers and IBM to support strategic priorities

  • Build your own database from complicated, real-world datasets, and apply robust statistical methods to produce actionable, data-driven insights

  • Use industry-standard software, such as Knime, Tableau, Hadoop and Spark, and engage with modern techniques including machine learning, AI, and Business Intelligence Modeling

  • Convert your existing study or workplace knowledge into a necessary skillset for modern data-driven careers

Accreditation

This course is accredited by the British Computer Society (The Chartered Institute for IT), partially meeting the educational requirements for CITP and CEng.

Career development

Careers this Master’s prepares you for

As a successful graduate of this course, you'll be able to show the enhanced skills in data science and analytics that companies need to extract the most valuable information from their data.

You'll have demonstrable experience with industry-standard software, and, if you choose to work with live company data in your studies, you'll have made professional contacts in the industry while making your analytical insights.

You'll also be an expert in new techniques and technologies in the field, with an eye for future developments, making you highly employable.

Graduates of this course have gone onto roles such as:

  • Senior data scientist

  • Data architect

  • Data officer

  • Information strategist

  • PhD research

Career outcomes shown are sourced from the latest available graduate outcome surveys. The data shows career outcomes at 15 months after graduation.

 

Entry Requirements

Qualifications or experience

  • A second-class honours degree in a relevant subject, or equivalent professional experience and/or qualifications.

English language requirements

  • English language proficiency at a minimum of IELTS band 6.0 with no component score below 5.5.

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Fees

For fees and funding options please visit website to find out more

Student Destinations

As a successful graduate of this course, you’ll be able to show the enhanced skills in data science and analytics that companies need to extract the most valuable information from their data.

You’ll have demonstrable experience with industry-standard software, and, if you choose to work with live company data in your studies, you’ll have made professional contacts in the industry while making your analytical insights.

You’ll also be an expert in new techniques and technologies in the field, with an eye for future developments, making you highly employable.

Graduates of this course have gone onto roles such as:

  • Senior data scientist
  • Data architect
  • Data officer
  • Information strategist
  • PhD research

Module Details

Core modules

  • Big Data and Machine Learning Applications – 30 credits
  • Business Intelligence – 15 credits
  • Data Management – 15 credits
  • Data Visualisation and Exploring Analytics – 15 credits
  • Intelligent Data and Text Analytics – 30 credits
  • Programming for Data Analytics and AI – 15 credits
  • Master’s Project – 60 credits

Optional modules

  • Business Intelligence - 15 credits
  • Cyber Security for Information Systems - 15 credits
  • Explainable AI - 15 credits
  • Statistical Machine Learning - 15 credits

 

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