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DD132U Fundamentals of Computer Science 6.0 credits

Information per course offering

Termin

Information for Spring 2024 Start 18 Mar 2024 contract education

Course location

KTH Campus

Duration
18 Mar 2024 - 3 Jun 2024
Periods
P4 (6.0 hp)
Pace of study

33%

Application code

60690

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

Contract education

Planned modular schedule
[object Object]
Schedule
Schedule is not published
Part of programme
No information inserted

Contact

Examiner
No information inserted
Course coordinator
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Teachers
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Course syllabus as PDF

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

Course syllabus DD132U (Autumn 2022–)
Headings with content from the Course syllabus DD132U (Autumn 2022–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Algorithms and data structures: A systematic overview of the concepts abstract data types, stacks, queues, lists, trees, searching, sorting and recursion based on the knowledge the students acquired in the course Fundamentals of programming. Hashing, priority queues, search trees, problem trees, text searching, simple syntax analysis, encryption and automata. Algorithm analysis.

Programming: Software development methodology, programme quality, abstraction, modularisation, testing, system calls, standard libraries.

Intended learning outcomes

Having passed the course, the student should be able to:

  • systematically test programs to discover errors,
  • use abstraction as a tool to simplify the programming,
  • choose appropriate algorithm to a given problem,
  • describe different algorithms for searching, sorting and encryption as well as their properties,
  • model problems using graphs and implement algorithms for searching in graphs,
  • implement and use basic data structures,
  • design and analyse simple algorithms with data structures,

in order to:

  • become a good problem solver using programming,
  • be able to use computational methods in application projects, and
  • acquire sufficient prior knowledge to be able to take advanced courses in computer science.

Literature and preparations

Recommended prerequisites

No information inserted

Equipment

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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

  • IND1 - Individual home assignments, 2.0 credits, grading scale: P, F
  • LAB1 - Laboratory assignments, 4.0 credits, grading scale: P, F

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

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

Technology

Education cycle

First cycle

Add-on studies

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