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DD2440 Advanced Algorithms 6.0 credits

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

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 avalg25 programme students

Course location

KTH Campus

Duration
8 Sept 2025 - 12 Jan 2026
Periods
P1 (1.5 hp), P2 (4.5 hp)
Pace of study

25%

Application code

50303

Form of study

Normal Daytime

Language of instruction

English

Course memo
Course memo is not published
Number of places

Places are not limited

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
Contact

Ioana-Oriana Bercea (bercea@kth.se)

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 2024–)
Headings with content from the Course syllabus DD2440 (Autumn 2024–) 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

  • explain different advanced algorithmic concepts such as randomized algorithms, approximation algorithms and fixed-parameter algorithms
  • analyse, select, use and verify algorithms that are based on the above concepts
  • develop efficient algorithms that are based on the above concepts
  • independently explore existing advanced algorithms, implement them and improve them using heuristics
  • communicate algorithmic ideas in a clear and formal way

in order to

  • design and evaluate computer programs that utilise computer resources efficiently.

Literature and preparations

Specific prerequisites

  • Knowledge in algorithms and complexity, 7.5 higher education credits, equivalent to completed course DD1352/DD2350/DD2352.
  • Knowledge in discrete mathematics, 7,5 higher education credits, equivalent to completed course SF1610/SF1630/SF1662/SF1679/SF1688.
  • Knowledge in probability theory and statistics, 6 higher education credits, equivalent to completed course SF1910-SF1925/SF1935.

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

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.

ÖVN1 consists of group tasks and individual assignments that are reported in writing and a group project that is reported in writing and orally.

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

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

Education cycle

Second cycle

Add-on studies

Please discuss with the instructor.

Contact

Ioana-Oriana Bercea (bercea@kth.se)

Supplementary information

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