This module introduces managers to how data is stored, integrated, and accessed within organisations. Participants gain a conceptual understanding of databases, data warehouses, and data lakes, along with hands-on exposure to querying data using SQL and Python. The emphasis is on asking the right questions of data, understanding query logic, and interpreting outputs rather than becoming programmers. Participants also see how ETL and integration tools support analytics workflows.

This module focuses on the often-overlooked foundations of analytics success—data quality, structure, and governance. Participants learn how business questions translate into data requirements, how poor data quality affects insights, and how features are conceptualised from a managerial perspective. The module also addresses ethical use of data, privacy regulations, and governance frameworks, enabling participants to balance innovation with responsibility and compliance.

This module develops the ability to convert analysis into insight and insight into action. Participants learn principles of effective data visualisation and how dashboards support managerial decision-making. Through demonstrations using Power BI, Tableau, and Python, the module shows how to design dashboards that highlight trends, comparisons, and anomalies. Special focus is placed on storytelling—how managers can frame insights, avoid misleading visuals, and communicate recommendations clearly to stakeholders.

This module provides a strategic foundation for understanding how analytics and AI create business value. Participants explore how organizations use data to build competitive advantage, enable digital transformation, and design new digital business models. The module clarifies the differences between traditional analytics and AI, introduces analytics and AI maturity models, and highlights leadership responsibilities in driving data-driven change. Emphasis is placed on accountability, governance, and cultural readiness so that managers can lead analytics initiatives responsibly and effectively.

This module develops the statistical intuition required for effective managerial decision-making using Excel, Python, and Generative AI tools. Instead of emphasising mathematical derivations, the focus is on interpretation, analytical judgment, and business relevance. Participants learn to summarise and visualise data, understand variability and uncertainty, test hypotheses, and distinguish correlation from causation. Regression analysis is introduced as a decision-support tool, with Excel- and Python-based illustrations and GenAI-assisted interpretation to help managers draw meaningful, actionable insights from data while retaining oversight and validation.

This module demystifies machine learning for managers by connecting models directly to business problems. Participants learn how predictive and prescriptive analytics differ from descriptive analysis and how business objectives translate into ML tasks. Core concepts of supervised and unsupervised learning are introduced, including regression, classification, clustering, and recommendation systems. The focus is on understanding model outputs, limitations, and business implications rather than technical model building.

This module expands the managerial lens to advanced AI applications such as deep learning, natural language processing, and generative AI. Participants explore how AI systems move from prediction to prescription and how organisations operationalise AI at scale. Critical issues such as explainability, bias, trust, and governance are discussed in depth. The module concludes with a leadership perspective on AI strategy, innovation, and sustaining competitive advantage in an AI-driven economy.

The campus immersion module provides an integrated learning experience that consolidates concepts from across the programme. Through discussions, demonstrations, and interactions, participants reflect on how analytics and AI can be applied within their own organisational contexts. This module strengthens peer learning, reinforces strategic thinking, and helps participants develop an actionable roadmap for applying programme insights after completion.