|
Please review this material on plagiarism first. It is essential you understand and adhere to our policies. The University has issued general guidance on plagiarism.
The programmes are each split into two elements: two semesters of lecture-based teaching, followed by a major individual project in a chosen specialist area. Together, these span a full twelve month period. The lectures are followed by examinations in December and/or April/May. Thereafter, students pursue their project work and write a dissertation on the project, this is assessed in August/September. Details of arrangements for projects will appear on the project pages. Once on course, it is possible to move to another MSc programme, subject to a range of constraints.
The Informatics Teaching Organisation (ITO) can help with all teaching admin issues, via the teaching contact form.
If you run into any difficulties during your course here (e.g.
health, personal, financial) then you should contact your MSc Directors
of Studies (Aris Efthymiou, Murray Cole, or Subramanian Ramamoorthy) see
http://www.inf.ed.ac.uk/teaching/years/msc/
for details of which students are assigned to which DoS. This is
extremely important. Your DoS will look to see what support we can
offer and importantly makes sure that any appropriate measures are put
in place in time for the Board of Examiners meeting/s (this is done in
confidence). Students are encouraged to report any such difficulties as
they occur and prior to the appropriate Board of Examiners meeting.
Information submitted after the completion of the Board of Examiners
process can only be considered via a formal appeal which could result
in lengthy delays to your study.
The Directors of Studies maintain a high level of
confidentiality and so any problems you discuss will not be aired
openly, your DoS will report that there is a 'problem' and its
severity, not divulging specific details unless absolutely necessary.
In addition to the feedback forms there is a regular staff-student meeting hosted by the Director of Teaching with the year representatives. Year reps are recruited at the start of the year, look out for emails on this if you want to get involved.
If you have an issue with a specific course, the normal action
would be to raise this directly with the course lecturer. We welcome
suggestions and constructive comments. If you feel unable to contact
the lecturer directly, talk to one of the year reps or, if required, to
the Course Organiser. They will forward your feedback in full
anonymity.
The University has issued a special bookmark for students which you can find on this page
that is useful to remind yourselves of feedback mechanisms. You can
either pick one up from the ITO or print it off yourself. More
information and guidance from the University on feedback can be found
on this page.
| Programme of Study | Available Specialist Areas |
| MSc in Artificial Intelligence | Intelligent Robotics Knowledge Management, Representation & Reasoning Learning from Data Natural Language Processing |
| MSc in Cognitive Science | Cognitive Science Natural Language Processing Neural Computation & Neuroinformatics |
| MSc in Computer Science | Analytical & Scientific Databases Computer Systems & Software Engineering Theoretical Computer Science |
| MSc in Informatics | No restrictions apply, you may choose from the full list of specialist areas. |
Students are required to be registered for 180 credit points at all times. This normally consists of 60 credit points in Semester 1 (including IRR), 60 credit points in Semester 2 (including IRP) and the final MSc Dissertation which is also worth 60 credit points. Further information about the compulsory courses (IRR and IRP) and specific programming requirements are explained later in this document. Once these constraints have been satisfied students have a free choice, as specified in the specialist area descriptions. You must select at least five courses from your specialist area.
In summary, you should:
For further advice, please contact your Specialist Area Advisor.
Each course is assigned a level, MSc courses are all level 11. In the timetable you will be able to choose from a restricted list of level 9 and level 10 courses (these are in italics). These are specifically designed for third year and fourth year undergraduates but may be of interest and value as part of an MSc programme. You are limited to a maximum of 30 credit points worth of these courses. If you want to take a level 9 course that is not listed anywhere in this document you should request permission from the Course Organiser. You do not have to take any level 9 or 10 courses.
A standard lecture course normally consists of up to twenty one-hour lectures (two per week for one semester) together with associated coursework and background reading. A few courses may also have tutorials, labs or a different structure. All courses have associated assignments, mainly assessed during the course - you will be given assignments to complete by deadlines set by the course lecturer. The relative weightings of the assignments and examination in the final mark for each course are given in the detailed course descriptions. Remember also that a substantial part of the assessment for most courses is by an exam which may ask questions related to any aspect of that course.
The Informatics lecture courses are worth either 10 or 20 credit points (nominally equivalent to 100 or 200 hours' student effort). Most courses in Informatics are 10 credit points but some 20 point courses are available to MSc students. You can take a maximum of two 20 point courses, again you do not have to take any.
Deadlines and changes
You may change course choices after the initial selection but there are deadlines. These are:
All MSc students must take the Informatics Research Review course in Semester 1 and Informatics Research Proposal course in Semester 2. These courses have no lectures and no exams and follow a different format. They are designed to introduce you to the research activity specific to your specialist area. Informatics Research Review gives you an opportunity to survey literature on a particular topic within your specialist area. Informatics Research Proposal allows you to build towards your summer research project. These courses have a simple PASS/FAIL grade only.
See also the programming requirement section as you may be required to take a course in programming skills.
The course choice constraints for each specialist area are shown below. You can find links to detailed course descriptions on the sortable course list. Core courses are listed in bold typeface, recommended courses (non-bold typeface) are suggested as particularly compatible with a specialist area, but not considered to be essential. You must register for 60 credit points of courses in Semester 1 and 60 credit points of courses in Semester 2. These must include 5 courses from your chosen specialist area, with the remainder coming from the pool of available courses (shown on the sortable course list).
Remember that the compulsory courses count as 40 credit points of your total 120 credit points. Students are responsible for making sure that their course selection is compatible with the published course timetable, many of the School's level 11 courses are scheduled together, meaning you can't fully participate in two courses that occupy the same timetable slot. We can do very little to avoid these clashes, but have made every effort to keep courses from the same specialist area apart. Please let us know if this turns out not to be the case, helping us avoid problematic clashes for future years.
| Range of Available Courses |
|
|
| Students registered in this Specialist Area must select at least fifty credit points from these courses, including any compulsory courses. | DIE - Data Integration and Exchange BIO1 - Bioinformatics 1 IAML - Introductory Applied Machine Learning PMR - Probabilistic Modelling and Reasoning EXC - Extreme Computing |
ADBS - Advanced Databases QSX - Querying and Storing XML TDD - Topics in Distributed Systems BIO2 - Bioinformatics 2 |
| Range of Available Courses |
|
|
| Students registered in this Specialist Area must select at least fifty credit points from these courses, including any compulsory courses. | BIO1 - Bioinformatics 1 SBM - Synthetic Biology: Modelling PM - Performance Modelling IAML - Introductory Applied Machine Learning NC - Neural Computation PMR - Probabilistic Modelling and Reasoning RL - Reinforcement Learning |
BIO2 - Bioinformatics 2 CSB - Computational Systems Biology MLCSB - Models & Languages for Computational Systems Biol. MLPR - Machine Learning and Pattern Recognition DME - Data Mining and Exploration |
| Range of Available Courses |
|
|
| Students registered in this Specialist Area must select at least fifty credit points from these courses, including any compulsory courses. |
CCS - Computational Cognitive Science IAML - Introductory Applied Machine Learning IVR - Introduction to Vision and Robotics CCS - Computational Cognitive Science ANLP - Advanced Natural Language Processing AR - Automated Reasoning CNL - Cognitive Neuroscience of Language HCI - Human-Computer Interaction NC - Neural Computation [PPLS] - Theories of Mind (20 points) [PPLS] - Computer Prog. for Speech and Language Processing [PPLS] - First Language Acquisition [PPLS] - Human Cognitive Neuroscience [PPLS] - Introduction to Mind, Lang. and Embodied Cognition [PPLS] - Language Production [PPLS] - Sentence Comprehension [PPLS] - Univariate Statistics and Methodology using R [PPLS] - Visual Word Recognition [PPLS] - Visual Attention [PPLS] - Visual Memory |
TCM - Topics in Cognitive Modelling ALE1 - Adaptive Learning Environments 1 AV - Advanced Vision CCN - Computational Cognitive Neuroscience MLPR - Machine Learning and Pattern Recognition NIP - Neural Information Processing NLG - Natural Language Understanding NLU - Natural Language Generation [PPLS] - Concepts and Categorisation [PPLS] - Multivariate Statistics and Methodology using R [PPLS] - Psycholinguistics [PPLS] - Simulating Language |
| Range of Available Courses |
|
|
| Students registered in this Specialist Area must select at least fifty credit points from these courses, including any compulsory courses. | CG - Computer Graphics CN - Computer Networking DAPA - Design and Analysis of Parallel Algorithms DS - Distributed Systems HCI - Human-Computer Interaction EAC - Energy-Aware Computing PM - Performance Modelling SEOC - Software Engineering with Objects & Component |
ADBS - Advanced Databases COPT - Compiler Optimisation PA - Parallel Architectures PPLS - Parallel Programming Language and Systems SAPM - Software Architecture Process and Management ST - Software Testing |
With the Informatics and Economics specialism students have the opportunity to study subjects at the intersection of these two fields that are growing closer together. The specialism is structured around a portfolio of courses from Economics and Informatics that focus on two streams:
Students can also mix courses from both streams.
The following table summarizes the set of courses available within the specialism. Course names in italics are level 9/10. [Econ] indicates that the respective course is taught by the School of Economics.
| Range of Available Courses |
|
|
| Students registered in this Specialist Area must select at least fifty credit points from these courses, including any compulsory courses. | [Econ] ESB1 - Economics of Strategic Behaviour 1 (20 points) [Econ] EE - Essentials of Econometrics (20 points) AGTA - Algorithmic Game Theory and its Applications PMR - Probabilistic Modelling and Reasoning IAML - Introductory Applied Machine Learning RL - Reinforcement Learning |
[Econ] AE- Applications of Econometrics (20 points) MLPR- Machine Learning and Pattern Recognition |
Note that students can take at most 30 credits of level 9/10 courses. Students should ordinarily take 40 credits of taught Economics courses and 40 credits of taught Informatics Courses (in addition to IRR and IRP). Students taking AE must also take EE as a prerequisite; and similarly students taking ISB must take either AGTA or ESB as a prerequisite.
A recommendation to students is to acquire knowledge in one of the two streams described above:
| Range of Available Courses |
|
|
| Students registered in this Specialist Area must select at least fifty credit points from these courses, including any compulsory courses. | IVR - Introduction to Vision and Robotics IAR - Intelligent Autonomous Robotics IAML - Introductory Applied Machine Learning PMR - Probabilistic Modelling and Reasoning PLAN - Automated Planning RL - Reinforcement Learning AGTA - Algorithmic Game Theory and its Applications CG - Computer Graphics GAGP - Genetic Algorithms and Genetic Programming |
AV - Advanced Vision SSRM - Structure and Synthesis of Robot Motion CAV - Computer Animation and Visualisation MLPR - Machine Learning and Pattern Recognition |
| Range of Available Courses |
|
|
| Students registered in this Specialist Area must select at least fifty credit points from these courses, including any compulsory courses. | AR - Automated Reasoning LP - Logic Programming HCI - Human-Computer Interaction IAML - Introductory Applied Machine Learning PLAN - Automated Planning AD - Applied Databases DIE - Data Integration and Exchange |
KMM - Knowledge Modelling and Management MASWS - Multi-agent Semantic Web Systems ALE1 - Adaptive Learning Environments 1 TCM - Topics in Cognitive Modelling SAPM - Software Architecture Process and Management |
| Range of Available Courses |
|
|
| Students registered in this Specialist Area must select at least fifty credit points from these courses, including any compulsory courses. | PMR - Probabilistic Modelling and Reasoning IAML - Introductory Applied Machine Learning NAT - Natural Computing AD - Applied Databases RL - Reinforcement Learning TTS - Text Technologies IT - Information Theory |
MLPR - Machine Learning and Pattern Recognition DME - Data Mining and Exploration CAV - Computer Animation and Visualisation SSRM - Structure and Synthesis of Robot Motion NIP - Neural Information Processing |
| Range of Available Courses |
|
|
| Students registered in this Specialist Area must select at least fifty credit points from these courses, including any compulsory courses. | [ACE] -
Sound Design Media [ACE] - Sonic Structures [ACE] - Real-Time Performance Strategies [ACE] - PG Musical Applications of Fourier Analysis IAML - Introductory Applied Machine Learning PMR - Probabilistic Modelling and Reasoning CG - Computer Graphics HCI - Human-Computer Interaction CCS - Computational Cognitive Science [PPLS] - Speech Processing |
MI - Music Informatics [ACE] - Interactive Sound Environments [ACE] - Digital Media Studio Project [ACE] - Non Real-Time Systems [ACE] - Electroacoustic Composition ALE1 - Adaptive Learning Environments 1 ASR - Automatic Speech Recognition TCM - Topics in Cognitive Modelling MASWS - Multi-agent Semantic Web Systems MLPR - Machine Learning and Pattern Recognition |
| Range of Available Courses |
|
|
| Students registered in this Specialist Area must select at least fifty credit points from these courses, including any compulsory courses. | ANLP - Advanced Natural Language Processing (20 points) IAML - Introductory Applied Machine Learning TTS - Text Technologies CNL - Cognitive Neuroscience of Language [PPLS] - Computer Prog for Speech and Language Processing [PPLS] - Language Production [PPLS] - Sentence Comprehension [PPLS] - Speech Processing [PPLS] - Univariate Statistics and Methodology using R [PPLS] - Visual Word Recognition |
ASR - Automatic Speech Recognition MT - Machine Translation MLPR - Machine Learning and Pattern Recognition NLG - Natural Language Generation NLU - Natural Language Understanding [PPLS] - Multivariate Statistics and Methodology using R [PPLS] - Prosody [PPLS] - Speech Synthesis |
| Range of Available Courses |
|
|
| Students registered in this Specialist Area must select at least fifty credit points from these courses, including any compulsory courses. | NC - Neural Computation BIO1 - Bioinformatics 1 PMR - Probabilistic Modelling and Reasoning RL - Reinforcement Learning AD - Applied Databases IT - Information Theory IRM - Informatics Research Methodologies [PPLS] - Statistical and Experimental Design |
CCN - Computational Cognitive Neuroscience CNV - Computational Neuroscience of Vision BIO2 - Bioinformatics 2 TCM - Topics in Cognitive Modelling NIP - Neural Information Processing |
| Range of Available Courses |
|
|
| Students registered in this Specialist Area must select at least fifty credit points from these courses, including any compulsory courses. | AR - Automated Reasoning DIE - Data Integration and Exchange PM - Performance Modelling AGTA - Algorithmic Game Theory and its Applications LA - Logic and Automata IT - Information Theory COC - Communication and Concurrency APL - Advances in Programming Languages ADS - Algorithms and Data Structures |
MLCSB - Models & Languages for Computational Systems Biology TDD - Topics in Distributed Databases CA - Computer Algebra CMC - Computational Complexity LSI - Language Semantics and Implementation QSX - Querying and Storing XML FPS - Functional Programming and Specification |
The programming courses you will need to take depend on your capabilities at the time you enter the course. There are two programming courses, both delivered in Semester 1: Introduction to Java Programmes covers Java, Logic Programing covers Prolog. Your choice of programming course(s) will depend on your prior experience, the requirement describe above (but see exemptions below), the other courses you wish to take (e.g. Prolog is required for some other courses, particularly in the areas of language, cognitive modelling and reasoning), and the type of project you expect to do in the second half of the course (some will require a specific language).
Exemptions: Students who already satisfy the requirement (at least to the extent that they would have no problem doing their MSc project in the relevant language) may be excused from taking one or more programming courses. Some students may enter the MSc already familiar with what we will consider as Java-equivalent (other object-oriented languages such as C++) or Prolog-equivalent (other AI-specific languages such as Lisp) and these can also be grounds for exemption from one or both language requirements.
Students you wish to claim exemption from the programming requirement, should obtain the approval by email from the appropriate specialist area advisor. In your email requesting exemption you should describe your past experience which you believe qualifies you for an exemption. The faculty member may ask you to go for a talk in person in some cases.The courses Topics in Cognitive Modelling (TCM, Semester 2) and Text Technologies (TTS, Semester 1) will be of interest to everyone, particularly students registered on the Artificial Intelligence or Cognitive Science programmes.
The School also runs two courses on Informatics Entrepreneurship (IE1 and IE2), and a course on informatics and climate change (Computational Methods for Global Change Research), that are open to all MSc students.You may also be interested in courses taught by another School, a sample of these courses appears here.
The MSc is examined on its taught component comprising coursework and examination and on the dissertation which you start immediately after the May exams. You must pass both the taught part and dissertation to pass on the MSc overall. If, for example, you achieve only Diploma level on the 120 point taught component of the course then you will not be allowed to undertake a project.
Coursework is delivered during the semester and where a course has 30% or less of the marks you should receive feedback and marks at the time. If the course has more than 30% of the marks from coursework, it will be treated as a term paper and not returned. All marks returned during the semesters should be treated as provisional until after the Board of Examiners meets after the main examination period.
In order to pass at MSc level, and continue onto the MSc project you must meet the following criteria:
Normally, you will not be allowed to submit coursework late.
If you have a good reason to need to submit late, you must do the following:
"Good reason" for an extension means something that, in the judgement of the member of staff responsible, would prevent a competent, well-organised, conscientious student from being able to submit on time. Examples include:
You should always inform your Director of Studies of any such thing that seriously affects your work, whether or not you ask for an extension as a consequence. If you prefer, you can choose to discuss details *only* with your DoS; s/he can advocate with other members of staff for you without going into details.
Non-examples, things that would not be considered good reasons, include anything you could have planned for or avoided: difficult clusters of deadlines, attending social events, the demands of any job you undertake during semester, last-minute computer problems, loss of work through (your) backup failure, etc.
In general, you are expected to plan your time well and including contingency time. For example, if you expect a piece of work to take two days, you should begin it more than two days before its deadline.
Note that this policy varies in other Schools and external courses may have different late submission rules.
Exams
Most examinations for the MSc courses in Informatics take place at the end of Semester 2. A small number of courses may examine in Semester 1, this may also be true of external courses. The correspondence between numerical scores, grades and their interpretation in terms of the MSc is given below.
| Score | Grade | Interpretation |
| > = 70 | A | Excellent |
| 60-69 | B | Very Good |
| 50-59 | C | Good |
| 40-49 | D | Satisfactory for Diploma but inadequate for MSc |
| < 40 | E | Unsatisfactory |
The Board of Examiners comprises the External Examiner, the Director of Teaching, the Course Organiser and the MSc course lecturers. Your overall taught mark is decided at a Board of Examiners meeting, usually held in at the end of May. The Board has the freedom to aggregate marks in any way but normally each paper is given equal weighting. The Board may take mitigating circumstances (e.g. illness) into account so it is vital that you communicate these to your Director of Studies, along with substantiating evidence (e.g. a medical certificate), if you believe that your performance has been impaired. If you are ill on or around the date of an examination then you must obtain a medical certificate from a doctor as soon as you are fit enough to do so. Your project mark is decided at a second Board of Examiners meeting in October, along with your overall MSc award. The Board of Examiners can award distinctions to students who have performed exceptionally well on both the taught (close to or above 70) and project (at least 70) components.
You have a right of appeal against a decision of the Board of Examiners. This must be made within six weeks of the release of results. The only grounds for an appeal are irregularities in the conduct of the assessment or the Board of Examiners not having all available information at the time of assessment without reasonable justification. If you have mitigating circumstances which would allow your results to be seen in a new light you should send these to the Board of Examiners rather than waiting for an appeal. To appeal, contact the Convenor of the Board of Examiners or your Director of Studies. Appeals should be directed to the Senatus Postgraduate Studies Committee.
University Assessment Regulations - see section 16 for regulations on academic appeals.
It is important to note that you will not be allowed to proceed to the project part of the course unless you have passed the taught component, it is therefore vitally important that the Board of Examiners is aware of any special circumstances in advance of the end of May meeting. Appeals will delay your start to the project unless you get special permission to start in advance of an appeal by the College Postgraduate Studies Committee.
If you have some condition for which you might be granted extra time in examinations (e.g. dyslexia), you should definitely contact the Disability Office in order to be assessed by the relevant University panel. It is also advisable to inform the Course Organiser at the start of the course. Assessment takes some time, so you should notify us as soon as possible.
For students who wish to leave early (immediately after the exams) or who do not achieve sufficient grades in their exams and coursework to proceed to an MSc project (still at least 40%) the degree of Diploma can be awarded. The Diploma course ends with the exams and there is no project or summer semester work.
The University has issued guidance on avoiding plagiarism
It is a natural and beneficial part of the educational experience for students to discuss their work with each other and to incorporate ideas from many sources into their work. However, there is an important difference between an acceptable use of other people's ideas and copying or sharing other people's work without attribution.
Further Informatics advice on plagiarism is available at: http://www.inf.ed.ac.uk/teaching/plagiarism.htmlFor assessment to be fair, the extent to which submitted work is your own must be clear. You must not plagiarise other people's work, presenting it as your own.
Plagiarism is a serious offence. It is often easy to detect. The School will use a number of detection methods to screen coursework. When plagiarism is detected, penalties appropriate to the problem will be applied, the Head of School will be informed as well as the College of Science and Engineering, and your academic record may be amended permanently.
Deliberately allowing your own work to be copied undermines the assessment process. Where there is collusion between students, all students involved may be penalised or disciplined.
|
Informatics Forum, 10 Crichton Street, Edinburgh, EH8 9AB, Scotland, UK
Tel: +44 131 651 5661, Fax: +44 131 651 1426, E-mail: school-office@inf.ed.ac.uk Please contact our webadmin with any comments or corrections. Unless explicitly stated otherwise, all material is copyright © The University of Edinburgh |
