Computer Science modules available to students from other departments (2012/13)
A selection of our modules are offered to students from other departments. Two kinds of module are available: (1) modules which are designed specifically for students throughout UCL; (2) modules from our normal degree programmes which might be suitable for non-Computer Science students.
- We sometimes have to limit the sizes of classes, so registration cannot be guaranteed.
Information is available via the UCL Online Timetable You should re-check your timetable regularly before the start of term to ensure that no last-minute changes have occurred. Every effort will be made to keep the timetable stable, but this can not be guaranteed.
Your choice of Elective Modules must be approved the External Students tutor and your home department. The approval of the External Students tutor is handled via a dedicated moodle module "Computer Science Elective Modules - Help and Guidance" <https://moodle.ucl.ac.uk/course/view.php?id=18720>
Only after your choice have been approved as explained in the moodle module, you can register the modules on Portico.
Registration for Computer Science ancillary modules is carried out on-line using PORTICO. You can log into PORTICO at www.ucl.ac.uk/portico. If you have technical problems logging on or registering with PORTICO, please contact the UCL Information Systems helpdesk.
If you require ACADEMIC advice about the suitability of a course, please contact Dr Jens Krinke, the computer science tutor for external students.
Malet Place Engineering Building
Please email Jens first to make an appointment.
Where to find us
The Computer Science department is in the Malet Place Engineering Building. The Departmental Office is on the 5th Floor.
How we get in touch with you
It is assumed that each student will have a UCL computer account and knows how to use email.
Each CS module has an associated Moodle page. Registration is normally automatic once you have registered for the module via Portico, however it is your responsibility to ensure that you are subscribed to all appropriate Moodle pages.
COMPC018, COMP6006 and COMP6008 are designed specifically for students throughout UCL. All of these are worth half a UCL credit (or 'half-unit'). Click on the links for syllabus details. These modules are sometimes over-subscribed. Prompt registration is advised.
This module provides students with all skills necessary to set up a hi-tech business making maximum use of the Internet, computing and accountancy software.
|A good standard of computer literacy|
This module is now FULL for 2012-13
This module aims to provide students considering careers in Investment Banking (such as Analysts, Traders and to a lesser extent, IT specialists) with an in-depth understanding of financial services and significant computing and statistical skills.
NOTE - this is a very popular option choice and only 80 places are available. Places are allocated on a first come first served basis. If you are rejected from the module please visit our further information page for advice.
|A good standard of computer literacy|
|COMP6008 Multimedia Computing||2|| |
This module focuses on content creation for the web and multimedia. The content creation covers HTML, Java Script, 2D and 3D image manipulation, audio and video, animation and tools such as Dreamweaver, Photoshop, Flash, Maya. The module contains a major practical element, and students will undertake a demonstration multimedia as a project. The target audience is students from across UCL who have a good level of computer literacy and should be particularly attractive to undergraduate students from the Arts and Humanities. As background, students are expected to have a strong foundation in personal computing skills.
|A good standard of computer literacy|
The following modules are taken from the Department's BSc and MSci/MEng programmes. These are the only such modules which may be taken by students from other departments. All of these are half-unit modules. Click on the links for syllabus details etc. Five places on each of these modules are reserved for students on the Physical Science programme registering on or before 28th September.
This module is now full for 2012/13
|1||Develop skills for analysing and evaluating theoretical arguments; develop programming and problem solving skills; to encourage a thoughtful approach to analysis and design problems.||A-level Maths or equivalent. Ability to program in Java.|
|COMP1004 Theory II||2||To develop programming and problem solving skills, to encourage a thoughtful approach to analysis and design problems, to familiarise students with logical and mathematical inference and argumentation.||1002 Theory I or equivalent|
|COMP1009 Cognitive Systems and Intelligent Technologies||1||The word 'cognitive' refers to perceiving and knowing. Cognitive systems explains the natural intelligence of humans in computational terms, in other words, thought processes and the use of knowledge are explained as information processing. As well as helping us understand the human mind, Cognitive systems contributes important models for building artificially intelligent systems, and it contribute to the design of tools we use to perform cognitive work. This module provides a general introduction to the key concepts, models and issues in cognitive science, with an emphasis on the contrasts between human and artificial intelligence.||A good standard of computer literacy.|
|2008 Logic and Database Theory||1||To introduce and familiarise students with logical and mathematical inference and with database theory, the latter having an emphasis on the fundamentals of relational database systems and SQL. Students learn syntax and semantics of first-order logic, various proof methods and elementary models of computation.||1002 Theory I, 1004 Theory II or equivalent|
Advanced and Master's level modules
The following level 3 and Master's level modules require strong and informed commitment from the students, who will be expected to have taken enough interest in the area to convince the Tutor that they have some idea of the subject area other than just by reading the syllabus.
|1||To address the theoretical and practical limitations of computation. To provide a theoretical framework for modelling computation. The concepts of undecidability and intractability are introduced through a number of examples. The module will convey the proof techniques that are used to classify problems and it is intended that students learn how to apply them in order to classify unfamiliar problems for themselves.||2008 Logic and Database Theory (or, exceptionally, other equivalent experience). Note that this module involves considerable logic and a definite degree of "mathematical maturity"|
|COMP3058 Artificial Intelligence and Neural Networks||2||The Artificial Intelligence section of this module introduces AI as both a technical subject and a field of intellectual activity. The overall targets are to present basic methods of expressing knowledge in forms suitable for holding in computing systems, together with methods for deriving consequences from that knowledge by automated reasoning, and to survey the general aims of AI and its links with other areas of Computer Science. The Neural Networks section of this module aims to give a general understanding of this new and rapidly-developing field, to equip students with the mathematical and conceptual tools which will give them access to the neural computing literature, to provide practical experience with neural network training and to promote a critical approach to the subject.||Familiarity with logic at the level guaranteed by any module in discrete mathematics (or in logic), plus some exposure to CS culture including at least one module in the use of a serious programming language.|
|COMP 3072 Image Processing (Also taught as: GV12 Image |
|1||The first half of this course introduces the digital image, describes the main characteristics of monochrome digital images, how they are represented and how they differ from graphics objects. It covers basic algorithms for image manipulation, characterisation, segmentation and feature extraction in direct space. The second half of the course proceeds to a more formal treatment of image filtering with some indication of the role and implications of Fourier space, and more advanced characterisation and feature detection techniques such as edge and corner detection, together with multiresolution methods, treatment of colour images and template matching techniques. The course allows students to explore a range of practical techniques, by developing their own simple processing functions either in a language such as Java and/or by using library facilities and tools such as MatLab or IDL. |
*Learning Outcomes:* To understand (ie be able to describe, analyse and reason about) how digital images are represented, manipulated, encoded and processed, with emphasis on algorithm design, implementation and performance evaluation.
|Successful completion of years 1 and 2 of Physical Science or |
Engineering programme with sufficient mathematical and programming content.
COMP M054 Machine Vision (Also taught as: GI14 Machine Vision)
Note: This is a Master's level module - the pass mark is 50%.
|1||The course addresses algorithms for automated computer vision. It focuses on building mathematical models of images and objects and using these to perform inference. Students will learn how to use these models to automatically find, segment and track objects in scenes, perform face recognition and build three-dimensional models form images.||Successful completion of years 1 and 2 of Physical Sciences or Engineering programme with sufficient mathematical and programming content.|