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Overview
The MPhil in Machine Learning and Machine Intelligence at the University of Cambridge aims to teach the state of the art in machine learning and machine intelligence; to give students the skills and expertise necessary to take leading roles in industry; and to equip students with the research skills necessary for doctoral study.
Learning Outcomes
By the end of the programme, students will have acquired:- a knowledge of the fundamental techniques in machine learning and how to apply these techniques to a range of practical problems;
- a deep understanding of fundamental problems in machine intelligence, including speech and language processing and computer vision, and the technologies that form the current state of the art;
- a comprehensive understanding of techniques, and a thorough knowledge of the literature, applicable to the area of their chosen research topic;
- presentation skills through presenting their research in progress;
- the methodological and other technical skills necessary for research in their chosen area;
- the ability to critically assess the technical literature in machine learning and machine intelligence and related topics;
- directly marketable skills in computing, machine intelligence, machine learning, and the data sciences;
- collaborative skills through working with other students on the practical exercises and with PhD students and research assistants while carrying out their research project;
- experience in large-scale computing for machine learning and machine intelligence; and
- an understanding of how to define and conduct a research project.
Continuing
Students wishing to apply for continuation to the PhD would normally be expected to attain an overall mark of 70 per cent.Programme Structure
Teaching- Students will spend the Michaelmas and Lent terms undertaking taught course modules. There will be an equivalent of ten full core modules, in addition to an elective option which can be chosen from a broad variety of modules.
- From mid-Lent term through the end of the course, students will conduct a substantial research project leading to a dissertation.
- The taught modules will be in a range of styles: traditional lecture courses, lecture courses with associated practical classes, reading clubs, and seminar-style modules. The course will emphasise coursework in several of the taught modules.
- Software projects aimed at implementing algorithms and modelling methods will be central to the practical modules and the research project.
Key information
Duration
- Full-time
- 11 months
Start dates & application deadlines
- Starting
- Apply before
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Language
English
IELTS 7
TOEFL® IBT 100
Credits
180 alternative credits
Delivered
On Campus
Disciplines
General Engineering & Technology Web Technologies & Cloud Computing Machine Learning View 238 other Masters in Machine Learning in United KingdomAcademic requirements
GPA Upper Second Class
English requirements
IELTS 7
TOEFL® IBT 100
Other requirements
General requirements
- Applicants for this course should have achieved a UK First class Honours Degree.
- If your degree is not from the UK, please check International Qualifications to find the equivalent in your country.
- Two academic references
- Transcript
- CV/resume
- Evidence of competence in English
Tuition Fee
To alway see correct tuition fees
-
International
37815 GBP/yearTuition FeeBased on the tuition of 37815 GBP per year during 11 months. -
National
15735 GBP/yearTuition FeeBased on the tuition of 15735 GBP per year during 11 months.
Living costs for Cambridge
846 - 1465 GBP /month
Living costs
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.
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