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DD2440 Advanced Algorithms 6.0 credits

Administer About course

Advanced course focusing on areas on the border between computer science and discrete mathematics and covering modern techniques for construction of efficient algorithms.

Information per course offering

Termin

Information for Autumn 2026 avalg26 programme students

Course location

KTH Campus

Duration
7 Sept 2026 - 11 Jan 2027
Periods

Autumn 2026: P2 (4.5 hp), P1 (1.5 hp)

Pace of study

25%

Application code

10138

Form of study

Normal Daytime

Language of instruction

English

Course memo
Course memo is not published
Number of places

Min: 1

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.
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

Course syllabus as PDF

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

Course syllabus DD2440 (Autumn 2026–)
Headings with content from the Course syllabus DD2440 (Autumn 2026–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

The course will describe and analyse a number of algorithms for combinatorial computational problems.

Algorithmic concepts: randomized algorithms, approximation algorithms, fixed-parameter algorithms.

Intended learning outcomes

After passing the course, the student should be able to

  • develop, analyze and verify efficient algorithms based on various advanced algorithmic concepts
  • independently investigate existing advanced algorithms, implement them and improve them using heuristics
  • present algorithmic ideas and problem solutions orally and in writing in a clear, formal and understandable manner

in order to be able to reason about and apply advanced algorithmic techniques to computational problems that may arise in future studies or professional activities.

Literature and preparations

Specific prerequisites

• Knowledge of algorithms and complexity, 7.5 credits, equivalent to completed course DD1352/DD2350/DD2352.

• Knowledge of discrete mathematics, 7.5 credits, equivalent to completed course SF1610/SF1630/SF1662/SF1679/SF1688/SF1698.

• Knowledge of probability theory and statistics, 6 credits, equivalent to completed course SF1910-SF1925/SF1935 or completed exam module TEN1 within SF1910/SF1925/SF1935.

Literature

You can find information about course literature either in the course memo for the course offering or in the course room in Canvas.

Examination and completion

Grading scale

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

Examination

  • ÖVN1 - Exercise, 6.0 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.

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

Students with disabilities, regarding any adapted examination for students with documented, permanent disabilities.

The examiner may allow a different examination form when re-examining individual students.

When a course is no longer given, students have the opportunity to be examined for two additional academic years.

ÖVN1 consists of group assignments that are presented in writing as well as individual assignments and a group project that is presented in writing and orally.

Examiner

Profile picture Ioana-Oriana Bercea

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/Theoretical Computer Science

Main field of study

Computer Science and Engineering, Information Technology, Information and Communication Technology

Education cycle

Second cycle

Supplementary information

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