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University of Gothenburg
Algorithms
The course topics are as follows: - Introduction. What is an efficient algorithm? - Tools for analysis of algorithms. O-notation. Analyzing loops and recursive calls. Solving recurrences; - Data structures and algorithms. Review of basic data structures; - Combining data structures. Merge-and-find; - Graph algorit…
- Higher education
- Information unavailable
- 18 January 2027
- GÖTEBORG
- Information unavailable
- 50 %
Overview
The course topics are as follows: - Introduction. What is an efficient algorithm? - Tools for analysis of algorithms. O-notation. Analyzing loops and recursive calls. Solving recurrences; - Data structures and algorithms. Review of basic data structures; - Combining data structures. Merge-and-find; - Graph algorithms; - Greedy algorithms; - Divide-and-conquer; - Dynamic programming; - Backtracking and Implicit search trees. Branch-and-bound; - Short introduction to local search and approximation algorithms; - Basic complexity theory. Complexity classes P, NP, and NPC, reductions. Examples of NP-complete problems. Coping with hard problems; - Short introduction to other design techniques: local search, approximation algorithms, randomized algorithms, preprocessing, network flow.
Admission scores
Entry requirements
One requirement is to have a bachelor's degree of 180 hec in computer science (or equivalent), or alternatively to have successfully completed courses corresponding to 120 hec in computer science or mathematics. The following requirements must also be satisfied: - 7\.5 hec in discrete mathematics (DIT980 Discrete Mathematics for Computer Scientists, or the sub-course Introductory Algebra of MMG200 Mathematics I, or equivalent), - additionally 10 hec in mathematics, - 15 hec in programming, and - 7\.5 hec in data structures (this requirement can be satisfied by the course DIT375 Python for Data Scientists). Applicants must prove knowledge of English: English 6/English level 2 or the equivalent level of an internationally recognized test, for example TOEFL, IELTS.
The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.
Source, measure and data quality
- Source
- Skolverket Susa-navet
- Period
- 2027-01-18
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.gu.dit093.86000.20271
- Last checked
- 2026-09-23T10:36:42.164498+00:00
- Limitation
- Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.
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About the provider
Sources and data quality
Education facts for the selected offering come from Skolverket Susa-navet.
Retrieved . Published . Times are shown in Swedish local time.
Source identity and publication version
- Publication version
- 8e217193-f5fa-4778-b085-a4521fd03e8d
- Education identity in the source
- i.uoh.gu.dit093.86000.20271
- Offering identity in the source
- e.uoh.gu.dit093.86000.20271
- Education-form source code
- HS
- Education code in the source
- DIT093
- Change time according to the source
- 2026-08-24T07:51:28
The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.