Our Msc Business Technology Management course is designed to meet the current IT needs of employers. Academic expertise in Data Science, Data Analytics, Machine Learning, Statistics and Cybersecurity are embedded throughout the modules.
You will develop skills and abilities in data management as well as learning to deal with real-world cybersecurity issues. On completing the course you will be equipped to deal with business' organisational data management requirements.
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.
- Fundamentals of Cybersecurity (30 credits)
Study a range of governance and management topics which will enable you to determine, establish and maintain appropriate governance, delivery and creation of cybersecurity solutions for information security, systems security and network security. Learn how to select the appropriate tools and techniques to address and manage concepts of risk, threats, vulnerabilities and potential attacks.
- Technology Management in Organisations (30 credits)
Discuss the management, organisation and use of cybersecurity and data science principles, policies and procedures in organisational settings. Contextualise technology management ecosystems related to cybersecurity and data science depending on your field of interest. 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.
- Machine Learning and Data Analytics (30 credits)
Study machine learning, data mining, and data analytics including relevant professional, ethical, social and legal aspects. Explore topics including 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.
- Masters Project (60 credits)
Undertake a real-world project through the support of a sponsor which includes both a research and practical element.