This module integrates advanced leadership theories with ethical management strategies, emphasising the practical skills needed to address complex organisational challenges. It cultivates ethical decision-making, shapes accountable leadership practices, and fosters sustainable and value-driven organisational cultures.

This module provides a critical overview of the core areas of marketing for organisations. It covers key concepts such as customer value, market analysis, and strategic marketing planning.

Students will explore key factors shaping the marketing environment, target marketing and consumer buyer behaviour, the importance and role of positioning and integrated marketing communications with an emphasis on the development and rationale for developing strong brands. Students will also examine the contemporary marketing challenges facing organisations students and how to evaluate marketing strategy.

This module equips students with adequate financial knowledge of corporate finance including investing, financing and dividend decisions in an organisational context. It aims to achieve the following objectives:-

1. To enable students to explore and develop an understanding of the theoretical techniques, concepts and methods employed in finance
2. To develop the ability to apply the theoretical to the practical, through the analysis of data and application of relevant techniques in the context of a variety of organisations
3. To evaluate and develop a critical and reflective awareness of the importance of the application of finance to decision making within organisations

Indicative contents include but are not limited to:

• Financial accounting – financial reporting/statements/corporate financing/financial control techniques/cash flow management
• Management and cost accounting – operational/implementation/strategic financial decision making/performance measurement
• Investment decisions – appraisal/risk/financing/capital rationing/strategy/acquisitions/rationing/strategy/acquisitions and mergers
• Value based management – shareholder value/valuation/ethical issues

This module develops high-quality managerial decision-making skills relevant to the contemporary business environment by focusing on the synthesis and interpretation of available data. Students will master key business analytics concepts, covering the essential process of acquiring and cleaning big data for subsequent analysis. The curriculum emphasises the application of descriptive, predictive, and prescriptive analytics to achieve strategic objectives. This approach equips learners with the skills to use core tools, statistics, basic programming, Machine Learning, and Artificial Intelligence (AI) techniques for forecasting and problem solving.

The module requires students to strategically evaluate and interpret data through activities such as utilising Generative AI for rapid market research, scenario planning, and financial forecasting. A critical element is understanding and learning to manage the risks and complexities inherent in data systems, including the need for strong cybersecurity protocols and managing data privacy (GDPR). The module also explores how to mitigate negative AI bias and instead apply "helpful bias" to align analytical outcomes with core organisational values, such as sustainability goals (ESG) and customer preferences. This ensures strategic decisions are informed by solid, ethically managed data analysis.

This module offers a detailed, technical exploration into the engineering, development, and implementation of advanced analytical and computational systems within finance. It moves beyond high-level strategy to focus on the underlying architectures and methods required to build and deploy modern data tools, including Generative AI.

Students will gain a specialist understanding of AI algorithms, covering the foundational principles of Neural Networks and Deep Learning, along with the practical steps necessary for creating accurate predictive models. Key technical skills include mastering methods for interpreting large volumes of unstructured data through Natural Language Processing (NLP) techniques such as Tokenization, Named Entity Recognition (NER), and Sentiment Analysis. The module also addresses the optimisation and automation of financial operations using AI-powered Robotic Process Automation (RPA) for complex tasks, including fraud detection and reconciliation.

The curriculum ensures readiness for future technology by investigating Decentralised Finance (DeFi) and Blockchain data structures, while also assessing the impact of Quantum Computing on cryptography and problem optimisation. A strong emphasis is placed on technical model management, including the mechanics of Prompt Engineering and the business value of fine-tuning Generative AI models for enhanced relevance and compliance in financial contexts.

A course of individual study and research project in accordance with established research principles involving the completion of a Management Research Project, usually in the form of a dissertation. 

The module is designed to enable learners to:

• Be able to identify & justify a Business research "real world" problems, evaluate, and apply appropriate research methods to address the research problem.
• Design and implement a management research project using methodologies and methods appropriate to
  research questions and objectives
• Analyse and report business/management research findings to meet academic and practitioner needs
• Demonstrate critical reflection on the research process, managerial implications and alignment with future study.
• Demonstrate the application of knowledge and skills to plan a substantial management research project.
• Assess and evaluate potential ethical and practical challenges to conducting a management research project.
• Provide students with the skills to develop the work from an existing research proposal into a piece of rigorous management research or an organisation-specific project using secondary or primary data as negotiated with their supervisor
• To provide students with the skills to write up an extended piece of research, demonstrating academic rigour, including consideration of methodological and ethical issues associated with the programme of academic research or the organisation specific project
• To enhance students' project planning, presentation, critical reflection, and analysis skills
• To support students with the opportunity, and the enabling mechanisms to support their development towards
  independent learning.

Indicative content includes, but is not limited to:

• The nature, extent and purposes of management research
• Management research paradigms
• Research strategies
• Research designs, methods and approaches
• Research quality standards: establishing validity, reliability and generalisability
• Sampling and Research instrument design
• Research ethics
• Research Data Management: collection, organisation and analysis
• Managing a dissertation research project