Taught course

Integrated Machine Learning Systems MSc

Institution
UCL - University College London · Electronic and Electrical Engineering
Qualifications
MSc

Entry requirements

A minimum of an upper second-class Bachelor's degree in electronic and electrical engineering, computer science, and related fields from a UK university or an overseas qualification of an equivalent standard. Basic knowledge (e.g. at UK 2:1 standard in relevant undergraduate-standard modules) of programming languages (such as C, C++, Python, Java, or similar) is required. Basic knowledge of mathematics (e.g. at UK 2:1 standard in relevant undergraduate-standard modules) is also required in algebra, analysis, probability, or statistics. Applicants must show an interest in developing thinking and problem-solving skills.

The English language level for this programme is: Level 1.

Further information can be found on our English language requirements page.

Pre-Master's and Pre-sessional English

UCL Pre-Master's and Pre-sessional English courses are for international students who are aiming to study for a postgraduate degree at UCL. The courses will develop your academic English and academic skills required to succeed at postgraduate level.

Months of entry

September

Course content

Join us on this one-year MSc for a full immersion into principles of data acquisition, analysis, security, and infrastructure. You will develop the expertise to excel in integrated machine learning systems engineering across start-ups, established companies, and research institutions.

Fees and funding

Please see UCL website for full information about fees and costs for this programme.

Qualification, course duration and attendance options

  • MSc
    flexible
    60 months
    • Campus-based learningis available for this qualification
    part time
    24 months
    • Campus-based learningis available for this qualification
    full time
    12 months
    • Campus-based learningis available for this qualification

Course contact details

Phone
+44 (0) 20 3370 1214