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Machine Learning, Data Mining and High- Performance Computing are concerned with the automated analysis of large-scale data by computer, in order to extract the useful knowledge hidden in it. Using state-of-the-art Artificial Intelligence methods, this technology builds computer systems capable of learning from past experience, allowing them to adapt to new tasks, predict future developments, and provide intelligent decision support. Bristol's recent investment in the BlueCrystal supercomputer - and our Exabyte University research theme - show our commitment to research at the cutting edge in this area.
This programme is aimed at giving you a solid grounding in Machine Learning, Data Mining and High-Performance Computing technology, and will equip you with the skills necessary to construct and apply ML, DM and HPC tools and techniques to the solution of complex scientific and business problems.
Skilled professionals and researchers who are able to apply these technologies to current problems, and thereby push the limits of what computers can effectively do, are in high demand in today's job market.
In the introductory week you will take a programming proficiency test and will be placed in either an 'experienced' stream or a 'foundation' stream.
This programme is updated on an ongoing basis to keep it at the forefront of the discipline. Please refer to the School website for the latest information.
Depending on previous experience or preference, students take units such as:
* Programming in C
* Image Processing and Computer Vision
* Learning in Autonomous Systems
* Introduction to Machine Learning
* Computational Genomics and Bioinformatics Algorithms
* Uncertainty Modelling for Intelligent Systems
* Cloud Computing
* Computational Bioinformatics
* Artificial Intelligence with Logic Programming
* Statistical Pattern Recognition
* High-Performance Computing
* Server Software
* Robotics Skills
* Research Skills
You must then complete a project that involves researching, planning and implementing a major piece of work. The project must contain a significant scientific or technical component and will usually involve a software development component. It is usually submitted in September.