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Course Structure

The MPhil in Machine Learning and Machine Intelligence is a 12-month programme running from October through to September of the following year. The programme will be offered only as a full-time course.

Students will spend the Michaelmas and Lent terms undertaking taught course modules. From mid-Lent term through to the end of the course, students will conduct a substantial research project leading to a dissertation.

Core Modules The course is based on a set of core modules to be offered by the Speech Research (SR) Group, the Computational and Biological Learning (CBL) Group, and the Computer Vision and Robotics (CVR) Group. One module is roughly equivalent to a 16 lecture course; both full and part modules will be offered. The core modules will give students an introduction to the field as well as a good understanding of advanced techniques and will prepare them to carry out their research projects.

Core Module Options For 2018-19, the optional modules are (1) Computer Vision and (2) Natural Language Processing. Students will pick one of the optional core modules.

Elective Module Students will pick one elective module from 4th year undergraduate and MPhil offerings.

Teaching methods Modules will be taught via traditional lecture courses, some with associated practical classes. The course will emphasize 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.

Research Project From the end of the Lent Term, students will undertake a research project leading to a dissertation and poster presentation. Projects are formulated and planned during Lent Term. A list of project options will be provided to students. These will be designed to ensure that the project is scoped correctly so that students can complete their project given the time, data, and computing resources available. The assumption is that students will choose from project topics proposed by the Faculty, however students with particular research interests will have the option of working with a member of staff to design and propose their own topic (with the approval of the Course Director).

Each student will have a project supervisor, and the project topics will be approved by the course management committee. The project is then carried out over the Easter and Research terms. Students will be expected to attend the CBL and Speech Group programmes of research seminars. The MPhil students will be integrated into the research groups in the Department and will work closely with PhD students and postdocs under the direction of the Project Supervisor. Projects will be evaluated on the basis of the dissertation of up to 15,000 words and a poster presentation.

Personal and Professional Development The MPhil offers many opportunities for the development of professional skills, giving students experience in preparing and giving presentations, report writing, collaborating in research teams, and carrying out literature searches. Students will also be expected to attend the invited seminar series run by the Machine Learning and the Speech Group.

Industrial Participation External speakers from industry (and academia) will be invited to the seminar series run by the Machine Learning and Speech Group. Industrial partners will from time to time participate in formulating and supervising dissertation research projects.

Assessment: In order to obtain a degree, students on the course will be required to obtain:
  • an aggregate mark of 60% or higher on the core and optional modules
  • a passing mark of 60% or higher on the dissertation
Taught modules will contribute to the aggregate mark either as a full module, or as a part module (with a weight of 50% or 75%). Module assessment is performed using various methods and sometimes more than one method as appropriate. These methods include unseen written tests, take-home tests, reports, practical write-ups, presentations, essays, demonstrations, or other exercises. For 4th year undergraduate modules (e.g. 4F10, 4F13), assessment will be as posted for those modules.

The overall course mark will be weighted 60% taught / 40% dissertation. Students achieving an exceptional performance will be awarded a Distinction. `Exceptional performance’ will be a mark of 75% or more in both components; a distinction may be awarded on the strength of a dissertation judged exceptional by the examiners. Cases of marginal failure (55%-59%) will be dealt with individually by the Examiners. Students failing the dissertation will be examined through a viva.