Skip to main content
Till KTH:s startsida Till KTH:s startsida

FCA3004 Computational Python 7.5 credits

The course provides the necessary foundations of computational Python to design algorithms and analyze data at research level.

About course offering

For course offering

Autumn 2023 Start 13 Nov 2023 programme students

Target group

No information inserted

Part of programme

No information inserted


P2 (7.5 hp)


13 Nov 2023
15 Jan 2024

Pace of study


Form of study

Normal Daytime

Language of instruction


Course location

KTH Campus

Number of places

Max: 12

Planned modular schedule


For course offering

Autumn 2023 Start 13 Nov 2023 programme students

Application code



For course offering

Autumn 2023 Start 13 Nov 2023 programme students


Olav Vahtras


No information inserted

Course coordinator

No information inserted


No information inserted
Headings with content from the Course syllabus FCA3004 (Autumn 2022–) are denoted with an asterisk ( )

Content and learning outcomes

Course disposition

The course comprises approximately 200 full-time study hours. The course includes lectures with associated individual home assignments where the student designs an efficient algorithm to solve a specific task. The assignments are presented and discussed during sessions scheduled for this purpose. (40 full-time study hours)

The course also includes a project where the student independently designs and presents a program written in Python thatintegrates efficient algorithm design with the student’s own research topic. (160 full-time study hours)

Course contents

  • Python and its relationship to other programming languages
  • Programming environments for Python
  • Version control with git
  • Software testing with pytest
  • Data science libraries: numpy, scipy, pandas, matplotlib
  • Interfaces to compiled languages
  • Relational and document-oriented databases with Python
  • ·Methods in Python for concurrent programming: threading, multiprocessing, and asynchronous methods

Intended learning outcomes

After completion of the course the doctoral student should have the knowledge and ability to

  • Write programs in Python to solve problems in computational science.
  • Apply best practices in programming with respect to version control and testing.
  • Choose and apply data-science libraries relevant for their problem domain.
  • Account for and apply established programming ethical guidelines.

Literature and preparations

Specific prerequisites

 Eligiblefor studies at the third-cycle level.

Recommended prerequisites

Basic Python or other equivalent programming experience.


No information inserted


Basic Python or other equivalent programming experience.

Examination and completion

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

Grading scale

P, F


  • DAT1 - Computer assignment, 2.5 credits, grading scale: P, F
  • PRO1 - Project, 5.0 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.

Additional information about the course and grade criteria are found in the course memo.

Other requirements for final grade

For final grade the following are required: Passed assignments, active participation in group discussions and passed written project report (PRO1). Participation in computer exercise with passed report (DAT1).

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted


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

This course does not belong to any Main field of study.

Education cycle

Third cycle

Add-on studies

No information inserted


Olav Vahtras

Transitional regulations

If the examination form is changed, the student will be examined according to the examination form that applied when the student was admitted to the course. If the course is completed, the student is given the opportunity to be examined on the course for another two academic years.

Additional regulations

Equipment: Own laptop computer.

Postgraduate course

Postgraduate courses at CBH/Theoretical Chemistry and Biology