该硕士课程获得英国计算机协会（BCS）的认可，旨在通过开发创新的计算智能应用程序的技能来满足对数据科学家的需求，该应用程序能够分析大量复杂数据，从而为企业决策和市场策略提供依据。多学科内容包括机器学习，神经网络，大数据分析，信息检索，云计算，模糊系统和进化计算。您将有机会进行实际项目，将您的学习应用于商业，金融，安全，工业控制，工程，自然语言处理，信息检索和生物信息学等现实问题。考文垂提供机会与活跃的研究人员一起学习普及计算，分布式计算和应用程序以及交互式虚拟世界的创新应用程序等领域。
This master's course aims to respond to the demand for data scientists with the skills to develop innovative computational intelligence applications, capable of analysing large amounts of complex data to inform businesses decisions and market strategies.<br><br>The main theme throughout this course is automatic big data processing and information retrieval through machine learning, neural network and evolutionary computing.<br><br>We aim to cover how to apply cutting-edge machine learning techniques to analyse big datasets, assess the statistical significance of data mining results and perform advanced data mining tasks.We will introduce you to important frameworks which may include Hadoop Map Reduce, Spark, applications of relational databases and NoSQL databases in combination with easy to use and powerful development tools such as Python and R.We will look at emerging theories, practices, approaches, and management of distributed and intelligent computing systems, examining a wide range of case studies to see how applications have been developed and for what purposes, such as steganography detection system for colour stego images.The focus of the course is on applications of data science methods and tools, combined with computational intelligence techniques for data-driven problem solving including the analysis, interpretation and visualisation of complex data, which is in increasing demand in fields such as marketing, pharmaceutics, finance, transportation, medicine, and management.You will have the option to apply for a work placement opportunity2, designed to further develop your skills and knowledge with the aim of maximising your employability prospects. See modules for more information.<br><br>1 year full-time