BSc (Hons) Data Science and Analytics Bachelor's degree at Westminster

This module aims to strengthen your mathematical skills and build proficiency in algebraic manipulation, equation solving, logarithms, matrix algebra, geometry, trigonometry, calculus, set theory, probability and statistics. The lectures will be interactive and supplemented with worked examples and demonstrations to help you apply these concepts to problems relevant to your courses.

This module provides an introduction to interactive and generative AI systems. You'll develop the skills to optimise the responses of generative AI and apply interactive AI systems to real-world problems.

This module provides a comprehensive introduction to data modelling and database architecture. It covers foundational concepts such as relational database modelling and the use of Entity-Relationship (ER) diagrams for conceptual and logical database design. You'll gain hands-on experience with Structured Query Language (SQL), learning to perform key operations, including creating, reading, updating, and deleting (CRUD) data within a database. Through a combination of lectures and practical compu

This module introduces key elements of probability and statistics and the application of statistical and data driven techniques. It covers descriptive statistics, the sampling probability distribution, estimation of probability and confidence intervals, initiation to hypothesis testing. A data oriented software tool is introduced and used to implement concepts and techniques: data processing, visualisation and analysis to solve small-scale problems. Principles of data collection, storage and dat

This module provides an introduction to computer programming in a high-level programming language. It concentrates on teaching the fundamentals of algorithm design and implementation using the Python programming language. You will develop practical programming skills and gain a foundational understanding of the underlying algorithms. The module will also cover the use of standard data structures and how to apply good programming practices in response to specific requirements.

This module introduces you to problem-solving through the design and implementation of algorithms using the Java programming language. It develops foundational programming skills with a strong emphasis on core object-oriented thinking, ensuring you learn how to structure and organise programs effectively. You will also explore the use basic data structures while applying sound programming practices in response to defined requirements.

This module introduces you to the Operational Research (OR) techniques, commonly used for business analytics, such as optimisation, forecasting, simulation and decision making. The module emphasises model formulation, evaluation and the translation of quantitative outputs into recommendations, with integrated appraisal of ethical and sustainability implications.

This module provides an applied understanding and practical experience of the data engineering pipeline to gather, understand, combine, clean, process and store data for further analysis. The module explores data pre-processing strategies and focus on both structured and unstructured data. Furthermore, the module covers issues related to data quality and governance, and metadata management.

This module is designed to equip you with the necessary skills to successfully undertake industrial projects in the IT and Data Science fields. It will develop the ability to apply project management and systems thinking methodologies to support the design and delivery of technical solutions in different global contexts. You'll be introduced to a range of contemporary development, testing and deployment strategies. You will gain valuable practical and professional experience working as part of a

This module enables you to create engaging data visualisations to effectively communicate results of data analysis to a diverse audience. You will learn how to encode information in visual form and will create infographics and dashboards. You will also learn to use the power of storytelling to create engaging data narratives.

This module helps you develop an understanding of, and gain hands-on experience in, the fields of machine learning and data mining. You will work through the full life cycle, from preparing data to validating and optimising learned models. You will explore different algorithms and approaches to machine learning and data mining, and consider the challenges of applying them to data sets of varying sizes and complexity.

This module teaches the foundations of business process management with a focus on analysing and optimising business processes using process mining and other cutting-edge techniques. You'll develop a practical understanding of how organisations operate and optimise workflows, preparing for roles where the ability to map, analyse and improve processes is crucial.

This module teaches Object-Oriented Programming (OOP), equipping you with the principles and practical skills needed to design and develop robust, modular, and maintainable software systems. Using Java and introducing the Spring Framework, you will apply core OOP concepts like class design and modularisation to create enterprise-level solutions. The emphasis is on clean architecture, focused implementation, and effective testing, preparing you to build reliable, scalable software in real-world e

This module provides a foundational understanding of sensing systems and signal processing, emphasising the role of integrated smart sensing devices and their interaction with computer systems. You'll explore the operational principles of standard sensors and transducers, including temperature, pressure, light, and motion sensors, as well as MEMS technologies. The course introduces key concepts in signal conditioning and processing, such as sampling, aliasing, Fourier transforms, and filtering t

This module requires you to integrate previously acquired knowledge and techniques with new insights gained through investigation and research, culminating in an extended piece of work. It involves the conceptualisation, design, implementation, and evaluation of a substantial solution, such as a software application, process, model, or experimental study. The module fosters independent working and encourages students to apply their learning to real-world challenges, supported by research, design

In this module, you'll be introduced to key analytical topics in Operational Research, focusing on both deterministic and probabilistic approaches to decision-making. It covers Deterministic Optimisation, Stochastic Processes and Game Theory. Topics include Linear Programming, Integer Programming, Network Models, Multi-Objective Optimisation. You'll explore these in depth, with an emphasis on model formulation and solution techniques. Additionally, Markov Chains, Markov Decision Processes, and G

This module provides an introduction to the cloud computing principles and practices essential for secure and scalable AI deployment. It covers foundational topics such as cloud computing fundamentals, AI deployment workflows, and the differences between on-premise and cloud-based solutions. Students will also explore key considerations in security, compliance, and governance, along with practical aspects of real-time versus batch inference, CI/CD, and model orchestration. Additionally, the modu

This module introduces you to data-driven approaches and emerging technologies transforming supply chain management. It highlights the importance of data-driven analysis and insights and how they can improve supply chain performance, support decision making and enhance efficiency, ethics and sustainability. You will learn to analyse supply chain data using analytical techniques and tools, to improve efficiency across supply chain processes such as inventory management and demand management.

The module will provide you with an understanding of the foundations of Artificial Intelligence and principal sub-fields of AI that have made significant impact, including but not limited to: Planning, Multi Agent Systems, Logic, Neural Networks, Evolutionary Computation, Computer Vision, Reinforcement Learning, Natural Language Processing, and Deep Learning. Each week an essential technique will be demonstrated via a complete implementation followed by a presentation of the theory and condition

This module provides practical knowledge of applying Large Language Models (LLMs) and Generative Artificial Intelligence (Gen AI) in real-world business applications, along with techniques and strategies for training, tuning, and deployment. It provides you with a technical foundation to help them bridge the gap between their taught knowledge in LLM and its counterparts' deployment in marketing, sales, finance, product, and more. You will learn the application of LLMs to transform business solut