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ED1100 Engineering Science 7.5 credits


This is a course in Engineering Science with emphasis on mathematical modelling, aimed to give the student skills in usage of mathematical models to treat and understand problems in technology and natural science. The course also treats the history of technology, the role of the engineer in society and related gender issues.

The course design is based on learning centred pedagogics. The examination is based on continual activity of the student.

(NASA Goddard photo)

Choose semester and course offering

Choose semester and course offering to see current information and more about the course, such as course syllabus, study period, and application information.


For course offering

Autumn 2024 CLGYM programme students

Application code


Headings with content from the Course syllabus ED1100 (Autumn 2024–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

  • The emergence of technology and the natural sciences.
  • Dynamic models of processes in nature.
  • Quantities, units and constants of nature
  • Methodology for construction of mathematical models.
  • Hypothetico-deductive research methodology.
  • Dynamic iterative system, non-linear systems and chaos.
  • Empirical and theoretical models.
  • Use of derivatives in modelling.
  • Graphic model fitting.
  • The least squares and Chebyshev methods.
  • Regression analysis of large data sets.
  • Sources of errors in modelling.
  • Estimates.
  • Judging reasonableness.
  • Analysis of edge cases.
  • Proportionality.
  • Dimensional analysis for checking computations and for finding new relations.
  • Simulation.
  • Differential equations in modelling.
  • The computer tools Python and Excel.
  • History of women's studies at higher technical education.
  • Conceptions of the engineer.
  • The roles of the engineer and the technology user from a gender perspective.
  • Introduction to oral communication and scientific writing.

Intended learning outcomes

After passing the course, the student should be able to

  • create mathematical models for given processes in the stages problem identification, assumptions, solution, interpretation, verification and implementation
  • construct and graphically represent theoretical and empirical models from empirical data
  • make estimates, check formulas and carry out dimensional analysis
  • use the computer tools Python and Excel as support in problem-solving
  • describe the main features of the historical development of technology and the natural sciences and discuss their relation
  • constructively reflect on the role of male and female engineers in society
  • show basic skills in communicating technology and natural sciences in writing and orally.

Literature and preparations

Specific prerequisites

Basic and specific requirements for engineering programmes.

Recommended prerequisites

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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

P, F


  • ANNA - Assignments, 4.5 credits, grading scale: P, F
  • ANNB - Assignments, 1.5 credits, grading scale: P, F
  • ANNC - Assignments, 1.5 credits, grading scale: P, 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.

Grading is on P/F scale (pass-fail)

Other requirements for final grade

Assignments, participation in seminars and lessons as well as presentations.

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

Electrical Engineering, Technology

Education cycle

First cycle

Add-on studies

No information inserted


Mathias Hoppe

Supplementary information

In this course, the EECS code of honor applies, see: