There is informal evidence of an ever-growing commercial demand for machine learning graduates. Machine learning can be used in any domain where fast, consistent and reliable decisions have to made given uncertainty and a huge amount of data. Data quality is often poor given the vast quantity collected by automated processes and sensors. Thus in an application-driven business world machine learning is often recognized as data mining.

On completion of the programme, graduates will understand the fundamental principles underlying the development and application of new techniques in this area, and be aware of the range and scope of algorithms and approaches available. They will be able to design, develop and evaluate appropriate algorithms and methods for new problems and applications, and be able to appreciate the advantages, disadvantages and limitations of different algorithms and approaches. At UCL, the MSc in Machine Learning combines a rigorous theoretical academic framework along with specific knowledge of a variety of application fields to fast-track your commercial career or to prepare for PhD research.

Possible future career paths include:

• Statistical Consulting

• Web Safety

• Business Intelligence

• Pharmacy Companies

• Finance

• Fraud Detection and Compliance

• Computer Vision

• Web Analytics

• Internet Start-Ups

More information on each of these can be found on our Course Webpages

'Joining the MSc in Machine Learning program has been a valuable experience, further developing my ability to think logically, assessing matters based on likelihood and impact. The developing nature of this area provides a platform for creativity and discussion. In addition, the opportunity to work with a great team of lecturers and other intelligent students created a fun, enlightening and spine-tingling experience.
After the graduation, I decided to join the Corporate and Investment Banking sector. I specialized in the Structured Property Finance whilst in the UK, and have recently switched to Project Finance, covering the Asia region from Hong Kong. The MSc in Machine Learning extended my logic and mathematics, which I have been using extensively in building financial models.'
Chi Chung Yuen, Associate, National Australia Bank, MSc in Machine Learning 2003/2004

'Very exciting and fullfilling year! I would never have hoped that teaching a machine to learn would generate such impressive results. The field of applications is incredibly broad, from fraud detection to medical diagnosis, to handwriting and voice recognition.

I am currently working as a software engineer at Schneider Electric, worlwide leader in electrical distribution and second in ultraterminal and secured power, since 2006 in the Innovation Department. I am involved in european projects focused on dynamic, service-oriented interoperable software platforms for home control and electrical distribution. I hope to evolve through various scientific R&D projects to build up a solid cross-domain, international experience.'
Sylvain Marié, Embedded Software Engineer Schneider Electric, MSc in Machine Learning 2005/2006

'Most of my class have moved onto PhD's or - as in my case - jobs, with one member now a lecturer!’
Bryan Feeney, web security research scientist at Scansafe, MSc in Machine Learning 2006/2007

‘Machine Learning Jobs are Growing on Trees’
John Langford, Director of Learning at Yahoo Research

‘I found the course extremely challenging in terms of both breadth and depth, and feel that it provided me with important new skills and knowledge.’
Tom Diethe, PhD student in the Department of Computer Science - MSc in Machine Learning 2005/2006

'Based on my experience, I find that the quality of the program is on a par with top-rate universities in the US and elsewhere. I highly recommend the program as both an educational experience and an excellent starting point for a career in several hot areas in academia or industry.'
Andreas Argyriou, Post-doctoral scientist - MSc in Machine Learning 2003/2004

‘The transferable skills I gained from the course have served me well in my new career, and have proved a good building block for me going into a career which is mainly based on economics.’
Louis Brown, MSc in Machine Learning 2005/2006

'I found the master a very challenging and fulfilling course. It gave me a wide scope of knowledge that allowed me to discovery a niche that really interested me. I began working on creating a robot snake that used shape changing metals as its motors and was controlled by Artificial Intelligence, specifically genetic algorithms.'
Siavash H. Mahdavi, Managing Director at Complex Matters

In my current PhD research, I found I have successfully transferred all the key skills from a theoretical context into a practical environment. An average day is spent working on the Statistical Multi-Lingual Analysis for Retrieval and Translation (SMART) project, which involves segmenting the sentences into phrases and building up a statistical model for the phrase translation. The thing I enjoy the most about this project is the successful application of my supervised learning knowledge and the statistical model I created. The work has also enabled me to develop extensive new competencies in perl or python as well as stochastic calculus. What is more, the comprehensive applications of the machine learning knowledge also make me possible to join the cross-subject projects. Last year we applied the kernel methods successfully on the fMRI data analysis and lead to our winning entry to the Pittsburgh Brain Activity Interpretation Competition (PBAIC) 2007. Looking for the future, the firm foundation acquired from my MSc. program allows me to go further in my research and study.'
Yizhao Ni, PhD student at the ISIS Group, Electronics and Computer Science, University of Southampton, MSc in Machine Learning 2005/2006