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DA2205 Introduction to the Philosophy of Science and Research Methodology 7.5 credits

About course offering

For course offering

Autumn 2024 scimet25 programme students

Target group

Open for all programmes from year 3 and for all master's programmes as long as it can be included in your programme.

Part of programme

Master's Programme, Machine Learning, åk 1, Mandatory


P1 (3.0 hp), P2 (4.5 hp)


26 Aug 2024
13 Jan 2025

Pace of study


Form of study

Normal Daytime

Language of instruction


Course location

KTH Campus

Number of places

Places are not limited

Planned modular schedule


For course offering

Autumn 2024 scimet25 programme students

Application code



For course offering

Autumn 2024 scimet25 programme students


Arvind Kumar, e-post:


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Course coordinator

No information inserted


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Headings with content from the Course syllabus DA2205 (Spring 2019–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

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

Specific prerequisites

No information inserted

Recommended prerequisites

Courses in Scientific computing (Numerical Analysis and Computer science).


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Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F


  • 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

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Opportunity to raise an approved grade via renewed examination

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Ethical approach

  • 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

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

Computer Science and Engineering

Education cycle

Second cycle

Add-on studies

AK2007 Computer Ethics, AK2001 Mathematics and Reality, AK2014 Decision Theory.


Arvind Kumar, e-post:

Supplementary information

In this course, the school's honor code is applied, see: