Algorithms and Data Structures III

5 credits

Course, Master's level, 1DL481

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
20 January 2025–23 March 2025
Language of instruction
English
Entry requirements

120 credits including 30 credits in mathematics including an introduction to linear algebra (Linear Algebra and Geometry I or the equivalent) and basic logic (Algebra I, Basic Course in Mathematics, or the equivalent), and 45 credits in computer science. Participation in Algorithms and Data Structures II. 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 12,083
  • Total tuition fee: SEK 12,083

Read more about fees.

Application deadline
15 October 2024
Application code
UU-61034

Admitted or on the waiting list?

Registration period
20 December 2024–27 January 2025
Information on registration from the department

Location
Uppsala
Pace of study
33%
Teaching form
On-campus
Instructional time
Daytime
Study period
20 January 2025–23 March 2025
Language of instruction
English
Entry requirements

120 credits including 30 credits in mathematics including an introduction to linear algebra (Linear Algebra and Geometry I or the equivalent) and basic logic (Algebra I, Basic Course in Mathematics, or the equivalent), and 45 credits in computer science. Participation in Algorithms and Data Structures II. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Admitted or on the waiting list?

Registration period
20 December 2024–27 January 2025
Information on registration from the department

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
19 January 2026–22 March 2026
Language of instruction
English
Entry requirements

120 credits including 30 credits in mathematics including an introduction to linear algebra (Linear Algebra and Geometry I or the equivalent) and basic logic (Algebra I, Basic Course in Mathematics, or the equivalent), and 45 credits in computer science. Participation in Algorithms and Data Structures II. 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 12,083
  • Total tuition fee: SEK 12,083

Read more about fees.

Application deadline
15 October 2025
Application code
UU-61034

Admitted or on the waiting list?

Registration period
5 January 2026–25 June 2026
Information on registration from the department

Location
Uppsala
Pace of study
33%
Teaching form
On-campus
Instructional time
Daytime
Study period
19 January 2026–22 March 2026
Language of instruction
English
Entry requirements

120 credits including 30 credits in mathematics including an introduction to linear algebra (Linear Algebra and Geometry I or the equivalent) and basic logic (Algebra I, Basic Course in Mathematics, or the equivalent), and 45 credits in computer science. Participation in Algorithms and Data Structures II. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Admitted or on the waiting list?

Registration period
5 January 2026–25 June 2026
Information on registration from the department

About the course

The course covers advanced techniques in algorithm analysis and design. Central topics for the course are the analysis of algorithm complexity, including NP-completeness, and design methods such as randomised algorithms and approximation. In addition, the course presents connections to modern research in algorithmics.

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