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.
Literature
See Absalon when the course
is set up.
Academic qualifications
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.
Teaching and learning methods
The course will mix
lectures, student presentations, and group work; the focus is on
the students' own projects and reports and individual
supervision.
Workload
- Category
- Hours
- Guidance
- 8
- Lectures
- 6
- Preparation
- 14
- Project work
- 178
- Total
- 206
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Continuing Education - click here!
Exam
- Credit
- 7,5 ECTS
- Type of assessment
- Written assignmentOral defence under invigilationGroup-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.
Course information
- Language
- English
- Course code
- NDAK12004U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 2
- Schedule
- B
- Continuing and further education
- Study board
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Computer Science
Course responsibles
- Christian Igel (igel@di.ku.dk)
Lecturers
Francois Lauze
Saved on the
30-04-2013