Course development and history
This course summarizes statistical and probabilistic methods used in applied Computer Science.
Select the semester and course offering above to get information from the correct course syllabus and course offering.
After passing the course, the student should be able to
in order to be able to make a degree project in sample-based inference methods.
No information inserted
For non-program students, 90 credits are required, of which 45 credits have to be within mathematics or information technology.
Courses in mathematics (analysis), programming, computer science and statistics equivalent to obligatory courses on D- or F-programme.Matlab or similar tool (Octave, R).
If the course is discontinued, students may request to be examined during the following two academic years.
A, B, C, D, E, FX, F
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability. The examiner may apply another examination format when re-examining individual students.
Written assignments and a project (INL1; 6 credits).
Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.
Computer Science and Engineering
Please discuss with the course leader.
Jens Lagergren, e-post: email@example.com
In this course, the EECS code of honor applies, see:http://www.kth.se/en/eecs/utbildning/hederskodex