NDAK12004U  CMM projects 2

Volume 2013/2014
Education
MSc Programme in Computer Science
Content
In the course, students
  • conduct a scientific project in computational and mathematical modelling (comprising pattern recognition, image analysis, machine learning, data mining, simulation, computer graphics, computational science, etc.), 
  • shall develop advanced scientific skills for project oriented work, and
  • wil be prepared for a Master's Thesis.
Learning Outcome

At course completion, the successful student will have:

Knowledge of selected methods for computational and mathematical modelling (comprising pattern recognition, image analysis, machine learning, data mining, simulation, computer graphics, computational science, etc.).

Skills for project oriented work in computational and mathematical modelling.
These skills cover all aspects of project work from initial brainstorming to reporting including

  • management of a small project,
  • relating own work to the existing body of knowledge;
  • experimental and/or theoretical study design;
  • recognizing the quality, perspectives, and limitations of achievements;
  • writing a scientific text of high quality in terms of both scientific content and presentation;
  • oral presentation of a project. 

Competences in

  • solving problems in the domain of computational and mathematical modelling;
  • managing, conducting, evaluating, and presenting scientific projects.
See Absalon when the course is set up.
We recommend that you have passed CMM Projects 1 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.
The course will mix lectures, student presentations, and group work; the focus is on the students' own projects and reports and individual supervision.
Credit
7,5 ECTS
Type of assessment
Written assignment
Oral defence under invigilation
Group-based projects with individual oral presentation followed by individual examination, graded on Danish ECTS-compliant 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. Submission in Absalon.
Exam registration requirements
Active participation in the course.
Marking scale
7-point grading scale
Censorship form
No external censorship
Re-exam
Resubmission at next reexamination period. In case of a failed group-project it will be resubmission of a individual report.
Criteria for exam assesment
See learning outcome.
  • Category
  • Hours
  • Lectures
  • 6
  • Preparation
  • 14
  • Project work
  • 178
  • Guidance
  • 8
  • Total
  • 206