Postgraduate Studentships - Search for funding opportunities.
Postgraduate Studentships - Search for funding opportunities.
Study Details: MSc 1 year full-time, 2 years part-time
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.
Qualifications or experience
English language requirements
For fees and funding options please visit website to find out more
If you meet our criteria, you could get a £3000 tuition fees discount – visit website for details
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:
All modules on this MSc Data Analytics are core.
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Wed 05 Jun 2024
