The main theme throughout this course is automatic big data analytics and natural language processing through machine learning, especially deep neural networks.<br/><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 analytics.<br/><br/><br/>- We will introduce you to important frameworks which may include Hadoop Map Reduce, Spark, applications of relational databases and NoSQL databases in combination with powerful languages such as Python and R.<br/><br/><br/>- 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.<br/><br/><br/>- 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.<br/><br/><br/>- 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/>