Masters Degree Description
The main theme throughout this course is automatic big data analytics and natural language processing through machine learning, especially deep neural networks.
- 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.
- 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.
- 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
Entry Requirements
Applicants for this programme will normally be expected to possess a minimum of a second class honours degree in Computer science, Mathematics or other relevant discipline.
Fees
For fees and funding options, please visit website to find out more
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