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Develop core data analysis skills and explore both traditional and state-of-the-art aspects of artificial intelligence and machine learning.
This research-led MSc takes a contemporary approach and covers the fundamental aspects of traditional symbolic and sub-symbolic aspects.
The programme will give you a solid awareness of the key concepts of artificial intelligence. You will also learn the techniques that form the current basis of machine learning and data mining. You will develop a wide-ranging skill set that supports further study or that you can use in application development.
As a result of the leading research being undertaken at Southampton, the course is able to offer a wide range of options that cover state-of-the-art modern techniques, which directly reflect research directions in ECS.
These include:
* intelligent agents
* complexity science
* computer vision
* robotics
* machine learning techniques, such as kernel methods and support vector machines
Key Facts
* We are ranked in the top three universities in the UK for computer sciences and IT
* Southampton is ranked in the top 51-100 universities for Computer Science in the 2013 QS World Rankings
* Southampton University has pioneered many of the most important advances in computer science and web technology of the past 10 years
Career opportunities
* Academia
* Bioinformatics
* Chemoinformatics
* Financial services
* Web applications
Programme Structure
The programme has been designed to maximise student choice by allowing you to tailor the structure to suit your own interests. You can choose areas that reflect your personal interests and work on an individual project. You will however, also take a number of compulsory modules to ensure you are exposed to key topics in all areas.
Modules
Semester 1
Core and Compulsory Modules
* COMP3032 Intelligent Algorithms
* COMP6008 Research Methods in Computing
* COMP6026 Evolution of Complexity
* COMP6031 Fndtns Art Intel
Optional Modules
* COMP3033Computational Biology
* ELEC3012Robotic Systems
* ELEC6122 Image Processing - MSc
Full Academic Year
Core and Compulsory Modules
* ELEC6103 TT Weekly Tutorial
Semester 2
Core and Compulsory Modules
* ELEC6121 Project Preparation
Optional Modules
* COMP3005Computer Vision
* COMP3008Machine Learning
* COMP6006Intelligent Agents
* COMP6028Semantic Web Technologies
* COMP6036Advanced Machine Learning
* COMP6041Computational Finance
* ELEC6024Advanced Computer Vision
* ELEC6087 Biologically-Inspired Robotics (A)
Modules not in Semesters
Core and Compulsory Modules
* COMP6029 MSc Project and Dissertation
Want to improve your English level for admission?
Prepare for the program requirements with English Online by the British Council.
- ✔️ Flexible study schedule
- ✔️ Experienced teachers
- ✔️ Certificate upon completion
📘 Recommended for students with an IELTS level of 6.0 or below.
Scholarships
Some students taking the course are sponsored by industry, while other students obtain financial support from local authorities, from professional institutions such as the Institution of Electrical and Electronic Engineers (IEEE) or from Career Development Loans. If you wish to obtain such sponsorship, you must make your own private arrangements.