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  • DeadlineStudy Details: 1 year-16 months full-time

Masters Degree Description

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.

Entry Requirements

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

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Fees

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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.

Module Details

Core:

Data Management - 15 credits
Intelligent Data and Text Analytics - 30 credits
Programming for Data Analytics and AI - 15 credits
Big Data and Machine Learning Applications - 30 credits
Data Visualisation and Exploratory Analytics - 15 credits
Masters Project - 60 credits

Optional modules:

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

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