Data Science and Analytics with Foundation BSc Honours

This module introduces the concepts of computing hardware and software, computer architecture and their uses for electronics and media. It also covers the fundamentals of computer networks, standards, protocols, interfaces and network security issues. The tutorial and laboratory exercises are designed not only to support the lectures but also to provide hands-on experience, skills and understanding of important aspects of computer systems and networks.

Critical thinking is fundamental to our ability to progress in an increasingly complex and changing world. It is an essential skill across a range of academic and practice-based disciplines.

This module helps you understand the importance and function of critical thinking both at university and beyond. By working in partnership with academic staff and peers, you will explore how critical thinking aligns with disciplinary practices, shapes scholarly knowledge, and addresses inequalities. Through problem-posing education and anti-racist practices, you will engage with real-world problems, fostering the ability to create a more just and sustainable world.

This module introduces practical mathematical and numerical problem solving relevant to computer science and engineering. Basic numeracy is revisited, and algebraic manipulation is revised and explored. Methods to take a real-world problem and to formulate and solve both symbolically and numerically are considered. Software tools will be used throughout. An applied, practical and real-world approach is taken whereby you'll gain skills to solve mathematical problems related to all areas of computer science and engineering gaining more confidence with numeracy related problems on your chosen course.

The module will be delivered with a combination of lectures and practical ‘hands on’ face-to-face tutorials. The material covered in this module will give you adequate necessary mathematical background to continue on any undergraduate course with the School.

This module introduces you to computer systems fundamentals and data systems fundamentals. An introduction to statistics is made and in particular how to gather, describe and visualise data collected through a survey or experiment. The aim of the module is to ensure that you have an understanding of the high-level systems and software that support data storage and retrieval to be able to work with such systems and to be able to critically and confidently operate with system stakeholders and technical partners such as data provider, storage, and data processing actors. Concepts of computer systems and data creation, storage, and retrieval systems will be introduced as well as compliance and security. This knowledge will be reinforced by practical sessions where you will create, store and retrieve data using standard tools, as well as have the opportunity to analyse and evaluate typical real-world data lifecycle scenarios. Also the module will provide practical experience in implementing databases and data querying in order to gain better understanding of data systems.

This module introduces you to the key academic, professional, and personal skills essential for success at university. It encourages good practices in writing, presentation, and time management, while also fostering reflection to help you build confidence as you transition to higher education. Open to all students enrolled in courses delivered through Westminster Foundation Pathways, the module provides a creative and supportive environment where you can reflect on and develop your academic and professional journey. You'll work with specialist facilitators who play a crucial role in guiding your academic and professional development.

With a focus on managing academic choices in a higher education setting, the module emphasises the importance of the United Nations Sustainable Development Goals (SDGs), using methodologies that prioritise equality, diversity, and inclusion. Through these lenses, you'll explore topics that prepare you to address real-world challenges as highlighted in the SDGs in a socially conscious, inclusive, and responsible manner.

This module introduces the concept of software. Students are introduced to the software development process and the design of simple programs firstly using visual methods of problem solving and then using a high-level programming language. The material covered in this module will give students a strong background and understanding to equip students to excel at Level 4 Programming modules.

This module provides the fundamental concepts and mathematical methods required in the Computer Games Development, Smart Computer Systems, Data Science and Analytics and Computer Network Security degrees. It aims to strengthen your mathematical skills and improve your fluency in algebraic manipulation, equation solving, matrix algebra, vectors, geometry, trigonometry, transformations, calculus and statistics. The lectures will be made interactive and interspersed with hands-on worked examples and demonstrations to consolidate your understanding of a variety of problems that relate 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 computing sessions, you'll become proficient in using standard database management systems and developing database-driven applications with practical programming examples. Additionally, the module explores contemporary Big Data technologies, introducing you to NoSQL databases and their applications in handling complex, large-scale data sets.

This module introduces the fundamental ideas of classical statistics. It covers descriptive statistics, the estimation of population moments using data and the basic ideas of statistical inference, hypothesis testing and interval estimation. It lays out the foundation for level 5 modules. Hence the topics such as data collection, data cleaning and data ethics are also covered.

An introduction to computer programming in a high-level programming language. The module concentrates on teaching the fundamentals of programming and algorithm design. Basic coding structures such as sequence, selection, and iteration will be covered. There will be an emphasis on practical exercises to develop programming experience and confidence.

The module aims to develop skills in the selection and implementation of problem-solving algorithms while learning the Java programming language. It will strengthen abilities in the implementation of algorithms, in terms of adherence to requirements, design and modelling, through to the application of sound programming principles. The understanding of structures and advanced programming methods will also be developed, including sorting, the implementation of classes and methods, as well as more sophisticated data structures such as lists, queues, and stacks.

This module introduces you to the Operational Research (OR) techniques, commonly used for business analytics, such as Linear programming, forecasting, simulation and decision making. It helps you to develop and analyse analytical models that support making effective business decisions.

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 team on a prototype solution on behalf of an external organisation.

This module enables you to create engaging data visualisations to effectively communicate the results of data analysis to a diverse audience. You'll learn how to encode information in visual form and will create infographics and dashboards. You'll also learn to use the power of storytelling to create engaging data narratives. We use a mixture of open source tools, such as R and ggplot2 and commercial tools, like Microsoft Power BI or similar.

This module provides an understanding and hands-on experience in the fields of machine learning and data mining, covering the full life-cycle from preparing data to validating and optimising the learned model. The module covers different algorithms and approaches to machine learning and data mining, and the issues of using them on data sets of different 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 will teach the fundamental ideas behind the object-oriented approach to programming. It will provide you with knowledge and practical experience in writing computer programs using object-oriented programming techniques. It will cover in a practical way the design and implementation of object-oriented software for software applications through the entire software development lifecycle.

This module is designed to provide an understanding of sensing systems and signal processing, including the use of integrated smart sensing devices and the integration of sensors with computer systems. This introductory module addresses the: operational principles of standard sensors and transducers; principles of signal conditioning; methods used for the post processing (data analytics) of captured sensory data. Furthermore the module discusses the operational principles and selection of data conversion devices such as analog to digital and digital to analog converters.

The module allows you to demonstrate in applied, written and oral forms the effective use of competences required to achieve the degree of study. It requires you to combine previously acquired knowledge and techniques, with new knowledge/ideas gained from investigation and research, and produce an extended piece of work related to the Data Science and Analytics BSc. It involves the conceptualisation, design, implementation and evaluation of a substantial piece of work which could consist of model(s), algorithm(s), software, process and/or experimental study.

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 Game Theory will be introduced at an introductory level to provide you with a foundational understanding of stochastic and strategic decision-making contexts.

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 module addresses model performance tracking, experiment management, and A/B testing, ensuring a comprehensive understanding of best practices in maintaining data quality, handling data drift, and achieving model reproducibility and versioning.

This module provides a comprehensive overview of operations management. You'll be introduced to the most relevant analytical methods and techniques to develop solutions supporting key operations management decisions.

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, Fuzzy 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 conditions needed to enable you to set up and use the techniques yourself.

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 the students 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.

Students will learn the application of LLMs to transform business solutions while ensuring their security, resiliency, ease of management, and integration with existing technology ecosystems.

Recent advances in AI and Machine Learning make traditional financial services more accessible and play a crucial role in promoting financial opportunities for businesses. You'll explore the significant impact of FinTech on businesses, industries and financial markets through real-life examples and case studies. You'll learn how FinTech is reshaping the future of finance industry by using innovations to meet the evolving needs of businesses and enhance your employability in FinTech related job roles.