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MSc Computational Statistics and Machine Learning Project (COMP0098)

Key information

Faculty
Faculty of Engineering Sciences
Teaching department
Computer Science
Credit value
60
Restrictions
Module delivery for PGT (FHEQ Level 7) available on MSc Computational Statistics and Machine Learning.
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

Aims:

To give students experience of undertaking and completing a large piece of work, applying techniques learned throughout the programme, including the technical skills of analysis, design and implementation.

Learning outcomes:

On successful completion of the module, a student will be able to:

  1. Work individually developing a major project.
  2. Plan and coordinate development activities.
  3. Make realistic work commitments.
  4. Present the work done effectively to a deadline.

Content:

There is no set syllabus: students identify their chosen project area and are allocated a supervisor who is a member of academic staff. The supervisor provides support and guidance.

The project runs from immediately after the examination period (May/June); students are responsible for organising themselves and their work, with advice from their supervisor. Students are expected to meet with their supervisor on a regular basis, as agreed with the supervisor.

Some projects are done in conjunction with other departments of the College, others are done in conjunction with external organisations subject to approval by the department. In all cases at least one supervisor must be from within the department who will provide as a minimum project management advice.

Project report:

  • The main report documents the results of the project. The deadline for submission is normally in early September.

Formatting details:

  • The dissertation text (defined as everything except title page, table of contents, references and appendices) should typically be between 30 and 100 pages in 12 point type and 1.5 or double spacing. The total dissertation length (main text together with appendices) should under no circumstances exceed 120 pages.
  • Students should place their code in an online repository and provide access details to it in their dissertation.
  • Writing the dissertation in LaTeX is optional, but strongly recommended.


Requisites:

To be eligible to select this module, a student must be registered on a programme and year of study for which it is a formally available.

Module deliveries for 2024/25 academic year

Intended teaching term: Terms 2 and 3 ÌýÌýÌý Postgraduate (FHEQ Level 7)

Teaching and assessment

Mode of study
In person
Methods of assessment
100% Dissertations, extended projects and projects
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
33
Module leader
Dr Dmitry Adamskiy
Who to contact for more information
cs.pgt-students@ucl.ac.uk

Last updated

This module description was last updated on 8th April 2024.

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