There are no average courses within our MSc programme. We are bound to provide an exceptional learning experience, and there is no better way to achieve this aim than with outstanding courses. They have been carefully crafted by experienced professors and are all meant to make you a more successful and efficient manager.
There are no old-fashioned exams. Instead you are given real-life case studies and essays, which allow you to think critically about your company and your own career. All this might seem too glossy but there is one catch: we do not accept average candidates. Only individuals as outstanding as our values can find their way toward admission at the Robert Kennedy College.
Induction
Not-for-credit module
A not-for-credit induction module will be the starting point of the programme. The induction process is designed to familiarise you with the programme design, requirements and resources, as well as with the way online interaction, learning and grading will take place. After the induction you should be familiar with academic life, including academic writing, library services and library access, OnlineCampus access, and academic support services.
Data Analytics
Aim of the Module
The aim of this module is to critically explore the range of concepts and functions of data analytics, including preparing and operating with data; abstracting and modelling an analytic question; and using tools from statistics, learning and mining to address these questions, evaluating the techniques dealing with how to go from raw data to a greater understanding of the patterns and structures within the data, to provision making predictions and decision making.
Intended Learning Outcomes
On successful completion, you will be able to:
- Critically evaluate current theories and practices in data analytics
- Critically analyse various practices in data analytics
- Evaluate and apply data analytics in a practical/business setting
Indicative Module Content
- Introduction to Analytics
- Principles of Data Science
- Data Science Practices, Impact, and Functions
- Modern Applications of Data Science
- Measuring Success through Data Science
- Digital Transformation Strategies
Artificial Intelligence
Aim of the Module
The aim of this module is to critically explore the range of concepts and functions of artificial intelligence in order to help develop a solid understanding of the guiding principles of AI, evaluating how the concepts of machine learning can be applied to real life business problems and applications.
Intended Learning Outcomes
On successful completion, you will be able to:
- Critically evaluate current theories and practices in artificial intelligence
- Critically analyse various practices in machine learning
- Evaluate and apply machine learning practices
Indicative Module Content
- Artificial Intelligence - Definition, concepts, paradigms. Application areas
- Problem Solving (Problem Representation, Uninformed and Informed Search)
- Knowledge Representation
- Artificial Neural Networks
- Machine Learning in Practice
- Commercial influences on AI revolution
Digital Marketing
Aim of the Module
The primary aim of this unit is to provide the student with a deep understanding of the issues facing digital marketing managers, by examining the strategically significant issues facing e-commerce such as environment and online marketplace, consumer behaviour and digital influence. The aim is to actively develop students’ knowledge of key marketing and digital marketing theories and apply this knowledge to strategic issues based on current research and industry practice, and facilitate the effective strategic decision making of a digital marketing professional.
Intended Learning Outcomes
On successful completion, you will be able to:
- Critically analyse the digital “playing field” and critically evaluate the value and relevance of different tools in practical situations
- Critically evaluate and develop the capability to think strategically about a company, its business position, and how its digital marketing strategy can be implemented and executed successfully
- Critically analyse key marketing and digital marketing theories, frameworks and tools and how this informs business strategies
Indicative Module Content
- Digital Marketing Channels
- Search Engine Marketing
- Content Marketing
- Influencer Marketing
- Content Automation
- Campaign Marketing
- Data-Driven Marketing
- E-Commernce Marketing
- Social Media and Mobile Marketing
- Display Advertising
- Digital Media
Information Management
Aim of the Module
This module enables you to develop a conceptual and comprehensive understanding of the manager's role in relation to the leading of the effective management and use of information, information technology and information systems and to apply these within both organisational and strategic contexts.
Intended Learning Outcomes
On successful completion, you will be able to:
- Reflect critically on the senior manager's role and responsibility in leading information governance within a service or organisation - with particular reference to data protection; record keeping and ensuring service user information is secure
- Perform a critical appraisal of the use of information systems in the context of ensuring effective flows of communication between services within the organisation
- Reflect critically on the use of information technology and information systems, in order to be able to support effectively staff development in line with organisational goals and to support service planning and decision making processes
- Appraise critically information systems used within your organisation or service, evaluating their effectiveness and suggesting any developments which could enhance the service.
Indicative Module Content
Information governance; the manager's lead role in ensuring information is secure; storage of information; data protection; record keeping; confidentiality and ethics in relation to information; Linux and open source software; communication within organisations and services; social networking - appropriate use of; supporting staff development. Flows of information between services. Cloud computing and software as a service.
Advanced Databases
Aim of the Module
The aim of this module is to critically explore the range of concepts and functions of database systems and data management, the fundamental concepts and essentials of the mechanisms that are used in both high-performance transaction processing systems (OLTP) and large-scale analytical systems (OLAP), evaluating both efficiency and correctness of the applications of these designs.
Intended Learning Outcomes
On successful completion, you will be able to:
- Critically evaluate current theories and practices in database systems and data management
- Critically analyse various practices in database systems and data management
- Evaluate and apply database systems and data management practices
Indicative Module Content
- Taxonomy of concepts. Applications of databases
- Data types and data storage. Database types. Data warehouses
- Database Management System Internals
- Query and transaction processing
- SQL (Structured Query Language)
- Optimisation strategies
Internet of Things
Aims of the Module
IoT, short for Internet of Things, is the ever-growing network of objects that use their data transmission capabilities to communicate with other devices over the Internet. This promises to create new business models, improve business processes and reduce costs and risks. The aim of this module is to critically explore the range of concepts and functions employed by IoT technologies while evaluating the efficiency and correctness of the applications of such designs.
Intended Learning Outcomes
On successful completion, you will be able to:
- Critically evaluate current theories and practices in IoT
- Critically analyse various practices in IoT
- Evaluate and apply IoT practices
Indicative Module Content
- IoT Introduction, brief history, trends
- IoT: Architectures, Design and Functionality, Standardisation
- IoT Security Concerns: Data and Privacy
- IoT Ethical and Social Implications
- Entrepreneurship and IoT
- IoT Applications: Use Cases
MBA Dissertation
Aim of the Module
This module provides an opportunity for students to use and extend the knowledge and skills acquired during the programme of study. Using appropriate research methodologies and data collection methods, they will critically synthesise a body of knowledge relevant to the taught programme.
Students must bias their dissertation to encompass the specific MBA for which they are studying; this will be carefully checked when the student’s proposal is being approved and a supervisor allocated. The research will usually be undertaken with respect to issues derived from organisations with which they work, or have worked.
Intended Learning Outcomes
On successful completion, you will be able to:
- Identify issues, research them in detail, analyse critically and synthesise data and ideas, with the aim of developing appropriate conclusions and recommendations
- Engage in critical reflection on the research process and the issues under investigation
- Address critically, develop and satisfy specific research questions based on a systematic and evidence-based approach
- Evaluate critically and present findings and recommendations in writing that confirm your understanding of the subject under investigation
Indicative Module Content
- The research question and hypotheses, justification, aim and objectives
- Research methodology, concepts, definitions
- Inductive and deductive concepts
- Qualitative and quantitative methods
- Inferential statistical analysis where appropriate
- Application of analytical tools using relevant and appropriate software packages
- Research design and ethics
- The research plan
- Content and structure of the dissertation