Business Intelligence – 10 ECTS
This module provides an introduction to the concepts of business intelligence (BI) as components and functionality of information systems. It explores how business problems can be solved effectively by using operational data to create data warehouses, and then applying data mining tools and analytics to gain new insights into organizational operations.
A detailed discussion of the analysis, design and implementation of systems for BI, including the differences between types of reporting and analytics, enterprise data warehousing, data management systems, decision support systems, knowledge management systems, big data and data/text mining. Case studies are used to explore the use of application software, web tools, success and limitations of BI as well as technical and social issues.
Learning Outcomes
- Describe the concepts and components of BI.
- DCritically evaluate the BI for supporting decision-making action.
- DDemonstrate the use of technologies and tools that make up BI.
- DAnalyse, design and implement the technical architecture that underpins BI systems.
Artificial Intelligence – 10 ECTS
To develop semantic-based and context-aware systems to acquire, organize process, share and use the knowledge embedded in multimedia content. The research will aim to maximize automation of the complete knowledge lifecycle and achieve semantic interoperability between Web resources and services. The field of Robotics is multi-disciplinary as robots are amazingly complex systems comprising mechanical, electrical, electronic H/W and S/W and issues germane to all these.
This module provides an introduction to artificial intelligence (AI). The list of topics may include artificial neural networks, search, planning, knowledge-based reasoning, probabilistic inference, machine learning, natural language processing, and practical applications.
Learning Outcomes
- Analyse what constitutes AI, the current trends and issues determining the effectiveness of AI technology.
- Ability to apply Artificial Intelligence techniques for problem-solving.
- Plan and implement an intelligent system using an AI technique.
- Investigate and deliberate upon a range of emerging AI technologies impacting future changes in the business industry.
Cloud Computing – 10 ECTS
This module introduces you to the core concepts of cloud computing. You gain the foundational knowledge required for understanding cloud computing from a business perspective and also for becoming a cloud practitioner. You understand the definition and essential characteristics of cloud computing, its history, the business case for cloud computing, and emerging technology use cases enabled by the cloud. We introduce you to some of the prominent service providers of our times (e.g. AWS, Google, IBM, Microsoft, etc.) the services they offer, and look at some case studies of cloud computing across industry verticals.
Learning Outcomes
- Understand the concepts, characteristics, delivery models and benefits of Cloud Computing and its architectures.
- Evaluate the service and deployment models, including technological drivers of Cloud Computing.
- Develop Cloud Computing solutions using service providers’ frameworks and open-source tools.
- Analyse the key technical and organisational challenges for cloud applications, including their risk assessment.
Operating Systems – 10 ECTS
This module will introduce you to modern operating systems. We will focus on UNIX-based operating systems, though we will also learn about alternative operating systems, including Windows. The module will begin with an overview of the structure of modern operating systems. Over the subsequent learning outcomes, we will discuss the history of modern computers, analyze in detail each of the major components of an operating system (from processes to threads), and explore more advanced topics in the field, including memory management and file input/output.
Learning Outcomes
- Explore different types of OS, their functions and user interfaces.
- Investigate the processes managed by an OS, including the scheduling algorithms and synchronization techniques.
- Explore the use of virtual and secondary memory management in OS.
- Demonstrate the use of the current OS used for business applications.
Additional Business Modules
Data Analytics – 10 ECTS
This module presents a gentle introduction to the concepts of data analysis, the role of a Data Analyst, and the tools that are used to perform daily functions. You will gain an understanding of the data ecosystem and the fundamentals of data analysis, such as data gathering or data mining. You will then learn the soft skills that are required to effectively communicate your data to stakeholders, and how mastering these skills can give you the option to become a data-driven decision maker.
Learning Outcomes
- Understand the use of statistical and other analytic tools and techniques to transform business data into coherent business objectives.
- Analyse the use of different analytical approaches to solve business problems and help in management functions.
- Utilization of data analysis to help decision-making in a business context.
- Analyse and communicate data findings effectively to all the stakeholders, orally and in writing.
Research Methods for Business – 10 ECTS
This module will introduce you to a range of research processes that will help to inform your choice of the research problem, research methodology, research methods, and data analysis.
You’ll start by examining how to define your research problem and build a search strategy to hone your initial scoping research so you don’t get overwhelmed with too many sources and too much information.
Learning Outcomes
- Determine and develop research scope, aim, objectives, and research questions, by
defining a specific business problem(s).
- Critically review the literature pertaining to the specific business problem(s).
- Demonstrate research skills required to understand research methodologies, and collection of primary and secondary data, including ethical considerations of research.
- Conduct and examine research data in a business context, by applying appropriate analytical tools to investigate the acquired data arrive at logical research findings, and communicate outcomes of the research project to identified stakeholders.