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Content and learning outcomes
Scientific knowledge, hypothesis testing, scientific texts, observations and experiment, explanation and laws, models and simulation, paradigms. Short history of computation and computers, writing technical reports and thesis reports, overview of important journals and textbooks, library search within some specific area.
Intended learning outcomes
The aim of the course is to provide a deeper understanding of the methodological and underlying philosophical issues that arise in science, in particular the computational sciences, and inspire to reflection on such issues within the student's own area of study. The course introduces key concepts in the philosophy and methodology of science such as knowledge, truth, belief, subjectivity, intersubjectivity and objectivity, causality vs. covariation, scientific explanation, the nature and epistemology of models and simulation, the path from science to policy, hypothesis testing, verifying and falsifying hypotheses, research ethics.
After having taken the course the student should be able to
- present the foundational issues in the methodology and philosophy of science, especially as regards the natural, technological and computational sciences.
- present the history of computation and computers
- do a library search within the subject
- write a technical report within the subject
Literature and preparations
Courses in Scientific computing (Numerical Analysis and Computer science).
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
- HEM1 - Assignments, 1.5 credits, grading scale: P, F
- HEM2 - Assignments, 3.0 credits, grading scale: P, F
- TEN1 - Examination, 3.0 credits, grading scale: 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.
Other requirements for final grade
Examination: (TEN1; 3 university credits)
Home assignments: (LAB1; 1,5 university credits, LAB2; 3 university credits)
Opportunity to complete the requirements via supplementary examination
Opportunity to raise an approved grade via renewed examination
- All members of a group are responsible for the group's work.
- In any assessment, every student shall honestly disclose any help received and sources used.
- In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.
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.Course web DA2205
Main field of study
AK2007 Computer Ethics, AK2001 Mathematics and Reality, AK2014 Decision Theory.
In this course, the school's honor code is applied, see: