|
| Udgave: |
Efterår 2012 NAT |
| Point: |
7,5 |
| Blokstruktur: |
2. blok |
| Skemagruppe: |
B |
| Fagområde: |
dat |
| Varighed: |
Full quarter |
| Omfang: |
3 hours of class time with a mix of lectures, seminars and group work. |
| Institutter: |
Datalogisk Institut |
| Uddannelsesdel: |
Kandidat niveau |
| Kontaktpersoner: |
Christian Igel, igel@diku.dk, tlf.: 21849673 |
| Andre undervisere: |
Francois Lauze |
| Skema- oplysninger: |
 Vis skema for kurset
Samlet oversigt over tid og sted for alle kurser inden for Lektionsplan for Det Naturvidenskabelige Fakultet Efterår 2012 NAT |
| Undervisnings- form: |
The course will mix lectures, student presentations, and group work with an outset in the students own projects and reports. Preparation time for the student is expected to be about 17 hours per week.
|
| Formål: |
The purpose of the course is to continue developing scientific skills for project oriented work in the content of Computational and Mathematical Modelling, and to prepare the student for the Master Thesis work.
|
| Indhold: |
The course includes all aspects of project work including from initial brainstorming to finishing report writing. Subtopics are project management, experimental planning, and scientific writing.
|
| Kompetence- beskrivelse: |
After course completion, the student will have obtained high degree of experience in central aspects of all phases of a scientific project, as well as be able to independently initiate and complete a project. |
| Målbeskrivelse: |
To get top grade the student must:
1. Manage a small scientific project
2. Put the produced work in perspective w.r.t. the scientific body of knowledge
3. Solve a selected problem of high Computational and Mathematical Modelling content and difficulty
4. Produce a set of experiments clearly demonstrating the quality of and highlights boundaries for the chosen solution.
5. Produce a scientific text of high quality both textually and scientifically.
6. The student must be able to make an oral presentation of own work. |
| Lærebøger: |
Notes |
| Tilmelding: |
Via KUnet from May 15th to June 1st. |
| Faglige forudsætninger: |
We recommend that you have passed CMM1 and several of the following courses: Statistical methods for machine learning, Signal and image processing, Constrained continuous optimization, Computational physics, Advanced topics in data modelling, Dataanalyse and Computergrafik. |
| Formelle krav: |
None |
| Eksamensform: |
Group-based project with individual oral presentation followed by individual examination, graded according to the 7-step scale with internal grading (intern censur). The examination covers the whole scope of the course (see topics and learning objectives), but with special emphasis on the subject of the written report.
Reexamination: Resubmission of original group based
project. The examination
format is as stated for the ordinary exam.
|
| Eksamen: |
Aflevering af projekt den 18. januar og mundtlig prøve den 25. januar 2013.
Reeksamen: Aflevering af projekt den 15. og mundtlig prøve den 19. april 2013.
|
| Kursus hjemmeside: |
 |
| Bemærkninger: |
Each week is organized as 3 hours of class time, which will be a mix of lectures, seminars and group work. Preparation time for the student is expected to be about 17 hours per week. |
| Undervisnings- sprog: |
Kun engelsk
|
| Sidst redigeret: |
24/5-2012 |