Algorithms and Data Structures II

5 credits

Course, Bachelor's level, 1DL231

Expand the information below to show details on how to apply and entry requirements.

Location
Uppsala
Pace of study
33%
Teaching form
On-campus
Instructional time
Daytime
Study period
3 November 2025–18 January 2026
Language of instruction
English
Entry requirements

60 credits of which 15 credits in mathematics and 25 credits in computer science. Alternatively 45 credits in the Master's Programme in Language Technology. Participation in Program Design and Data Structures of which 9 credits shall be completed, alternatively participation in Algorithms and Data Structures I. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Selection

Higher education credits in science and engineering (maximum 240 credits)

Fees
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.
  • First tuition fee instalment: SEK 10,833
  • Total tuition fee: SEK 10,833

Read more about fees.

Application deadline
15 April 2025
Application code
UU-11016

Admitted or on the waiting list?

Registration period
20 October 2025–9 November 2025
Information on registration from the department

Location
Uppsala
Pace of study
33%
Teaching form
On-campus
Instructional time
Daytime
Study period
3 November 2025–18 January 2026
Language of instruction
English
Entry requirements

60 credits of which 15 credits in mathematics and 25 credits in computer science. Alternatively 45 credits in the Master's Programme in Language Technology. Participation in Program Design and Data Structures of which 9 credits shall be completed, alternatively participation in Algorithms and Data Structures I. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Admitted or on the waiting list?

Registration period
20 October 2025–9 November 2025
Information on registration from the department

About the course

The course extends and deepens your knowledge about algorithms and their analysis. After the course, you can design algorithms based on techniques such as dynamic programming and greedy algorithms, as well as derive their complexity from recursive equations. List of topics:

  • solving recursive equations that describe the algorithm's complexity
  • dynamic programming
  • greedy algorithms
  • graph algorithms: minimum spanning trees, shortest paths
  • string matching.

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