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ED1100 Engineering Science 7.5 credits

Administer About course

 

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)

Information per 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.

Termin

Information for Autumn 2025 CLGYM programme students

Course location

KTH Campus

Duration
25 Aug 2025 - 24 Oct 2025
Periods
P1 (7.5 hp)
Pace of study

50%

Application code

50914

Form of study

Normal Daytime

Language of instruction

Swedish

Course memo
Course memo is not published
Number of places

Places are not limited

Target group

CLGYM year 1, but also open for all programs, as long as it can be included in your program.

Planned modular schedule
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Schedule
Schedule is not published

Contact

Examiner
No information inserted
Course coordinator
No information inserted
Teachers
No information inserted
Contact

Mathias Hoppe

Course syllabus as PDF

Please note: all information from the Course syllabus is available on this page in an accessible format.

Course syllabus ED1100 (Autumn 2024–)
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.

Equipment

No information inserted

Literature

No information inserted

Examination and completion

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

Grading scale

P, F

Examination

  • 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

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

Profile picture Mathias Hoppe

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

EECS/Electrical Engineering

Main field of study

Electrical Engineering, Technology

Education cycle

First cycle

Add-on studies

No information inserted

Contact

Mathias Hoppe

Supplementary information

In this course, the EECS code of honor applies, see:
http://www.kth.se/en/eecs/utbildning/hederskodex.