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. 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:
- Data Science Fundamentals (30 credits)
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.
- Data Science Product Development (30 credits)
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.
- Machine Learning and Data Analytics (30 credits)
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
- Technology Management for Organisations (30 credits)
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.
- Computing Masters Project (60 credits)
Develop a practical deliverable and investigate an area of academic research through the support of a sponsor for example: an IT strategy; an investigative study; a technically challenging artefact (e.g. a feasibility study, design, implementation, re-engineered solution); or undertake a theoretical review based on a novel research question (provided by a research active member of staff). Underpin the project with a literature review that is a conceptual framework of your study - a systematic synthesis of concepts, assumptions, expectations, beliefs, and theories that supports and informs your research.