MSc Big Data and Text Analytics

What fascinates you? Apply your learning in computer science or engineering to solve a problem. Design, implement and evaluate a solution, producing a dissertation on your investigation and giving an oral presentation of your work. Test your knowledge, while gaining practical experience and building your project management skills.

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Search engines have become the first entry point into a world of knowledge and they form an essential part of many modern computer applications. While much of the underlying principles have been developed over decades, the landscape of search engine technology has changed dramatically in recent years to deal with data sources magnitudes larger than ever before (the rise of 'big data'). As a result of this, new paradigms for storing, indexing and accessing information have emerged. This module will provide the essential foundation of information retrieval and equip students with solid, applicable knowledge of state-of-the-art search technology.

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Teamwork skills are essential for employability. The aim of this module is to provide students with the opportunity to apply their specialised knowledge to a realistic problem and gain practical experience of the processes involved in the team-based production of software. Wherever possible, teams are organised on the basis of shared interest, and the problem is designed to exercise their understanding of their area of specialised study. Starting from an outline description of a realistic problem, each team is required to develop a fully implemented software solution using appropriate engineering and project management techniques.

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Humans can often perform a task extremely well (e.g., telling cats from dogs) but are unable to understand and describe the decision process followed. Without this explicit knowledge, we cannot write computer programs that can be used by machines to perform the same task. “Machine learning” is the study and application of methods to learn such algorithms automatically from sets of examples, just like babies can learn to tell cats from dogs simply by being shown examples of dogs and cats by their parents. Machine learning has proven particularly suited to cases such as optical character recognition, dictation software, language translators, fraud detection in financial transactions, and many others.

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As humans we are adept in understanding the meaning of texts and conversations. We can also perform tasks such as summarize a set of documents to focus on key information, answer questions based on a text, and when bilingual, translate a text from one language into fluent text in another language. Natural Language Engineering (NLE) aims to create computer programs that perform language tasks with similar proficiency. This course provides a strong foundation to understand the fundamental problems in NLE and also equips students with the practical skills to build small-scale NLE systems. Students are introduced to three core ideas of NLE: a) gaining an understanding the core elements of language--- the structure and grammar of words, sentences and full documents, and how NLE problems are related to defining and learning such structures, b) identify the computational complexity that naturally exists in language tasks and the unique problems that humans easily solve but are incredibly hard for computers to do, and c) gain expertise in developing intelligent computing techniques which can overcome these challenges.

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This module aims to prepare students for conducting an independent research project leading to a dissertation and to provide them with an appreciation of research and business skills related to their professional career. As a precursor to their project students, individually select an area of Computer Science, or Electronic Engineering, or Computational Finance and perform the necessary background research to define a topic and prepare a project proposal under the guidance of a supervisor. The module guides them by a) introducing common research methods b) creating an understanding of basic statistics for describing and making conclusions from data c) helping to write a strong proposal including learning how to perform literature search and evaluation and d) giving an in-depth view into the business enterprise, financial and management accounting and investment appraisal.

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We live in an era in which the amount of information available in textual form - whether of scientific or commercial interest - greatly exceeds the capability of any man to read or even skim. Text analytics is the area of artificial intelligence concerned with making such vast amounts of textual information manageable - by classifying documents as relevant or not, by extracting relevant information from document collections, and/or by summarizing the content of multiple documents. In this module we cover all three types of techniques.

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The aim of this module is to familiarise students with the whole pipeline of processing, analysing, presenting and making decision using data. This module blends data analysis, decision making and visualisation with practical python programming.Students will need a reasonable programming background as they will be expected to develop a complete end-to-end data science application.

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This course gives an introduction to computer security and cryptography, and then goes on to consider security as it relates to a single, network connected, computer. Introductory material is independent of any operating system but the consideration of tools will focus on those available for Linux, partly because its open-source nature facilitates this and partly because it is widely used on server systems. The introduction to cryptography will be used to consider its use in encryption and authentication.

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Acquire critical and transferable skills associated with the creation and growth of new business ventures. You focus on the development process from start up to early stage growth of new ventures, new small businesses spin offs from large firms, and especially innovative, technology-based firms. You study opportunity identification, self-efficacy, ideas generation, bricolage and bootstrapping, developing business models, networking, marketing, and finance.

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A huge industry has grown up in the last few years delivering a wide range of apps for mobile devices, including application areas such as games, social networking, information, and productivity. Given the power of modern mobile devices coupled with their range of inputs (audio, camera, GPS, motion sensor, touchscreen) this creates an exceptionally interesting platform to develop applications for. Furthermore, these platforms come complete with their own marketplaces meaning that successful applications can achieve a large market share based largely on their merit. The purpose of this module is to teach the main aspects of programming applications for such devices. Such a course could be taught at an abstract level, independent of the particular type of device in question, but the approach taken on this module is to explore one particular platform (Android), in a hands-on and in-depth manner. This is a popular platform with a range of excellent devices (including low cost ones) from a variety of manufacturers. The platform is well designed and well documented, and has the significant advantage of being Java based, meaning that students can get up to speed relatively quickly and concentrate on the interesting issues involved in developing a high quality app without having to learn a new language at the same time.

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