The UK Government has identified a huge shortage of specialists in data science and artificial intelligence. The University of Sunderland is looking for a new generation of idealists, visionaries and problem solvers to help business, industry and government make the right decisions in our increasingly complex and uncertain world.
This course is designed for students who have computing, STEM experience or prior experience in working with data (e.g. statistics), to gain the knowledge and skills required to work in data science or data analytics in the real world. We want you to bring your background with you, whether you graduated in Psychology, Business, Geography or Law. We are looking for people who ask questions, who don’t jump to conclusions, and who respond with caution. We want people who are able to find and communicate the best possible solutions.
On this course, you'll study subjects including the fundamentals of data science, data mining, machine learning, data analytics and visualisation, and security of big data. In addition, you'll have the opportunity to undertake a placement (subject to availability) and put your skills into practice, enhancing your employability. You can find your own placements or develop professional practice projects, working in our Digital Incubator or research-based projects with one of our academic research teams.
This highly practical course means you’ll have the opportunity to experience the latest technologies and tools used in industry, giving you the confidence to be productive and effective when you go out into the workplace.
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Modules on this course include:
Learn how to use different types of data and understand how to fuse more than one dataset together. Apply a full range of traditional and intelligent analytics to a variety of datasets and make use of modern data science / big data platforms and languages. Cover techniques and tools for presenting and visualisation.
Learn how to design and develop a data science product to solve a challenging real world problem, based on a systemic literature review on state of the art data science software technologies and project development methodologies, prototyping the product with end users’ evaluations. Produce a project summary report.
Study three interrelated subjects: machine learning, data mining, and data analytics including relevant professional, ethical, social and legal aspects. Focus on information and knowledge management, problems with data, approaches to selection of data analytics tools, principles of modelling and simulation, and operations research. Examine the trends, tools, and current developments in the area of machine learning, data mining and data analytics and their practical applications
Learn to apply the principles, policies and procedures of cybersecurity and data science to provide resilient and robust organisational solutions for secure and valuable information. Develop techniques and use tools that will enable you to undertake critical analysis of the challenges and opportunities of using cybersecurity to mitigate and manage risk to data and enable business continuity in the case of data breaches. Develop a critical understanding of governance, standards, audit, assurance and review in order to evaluate the challenges in managing technology.
Job trends data shows a 15,000% increase in the job prospects between 2011 and 2012, recognising big data as the ‘next big thing’ to revolutionise how we work, live and communicate (Indeed, 2016).
Progress in some of the most attractive fields and industries, including government agencies, high technology companies, consulting and market research firms. Benefit from the University’s close links with businesses and employers in the North East and join an industry-driven programme.
Businesses and industries across the UK have identified a skills gap in data science and currently the role of a Data Scientist is one of the highest paid jobs in the computing discipline.
Insurance-Single: 300 GBP/year