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Data Structures and Algorithms (4op)

Toteutuksen tunnus: AE00CM74-3004

Toteutuksen perustiedot


Ilmoittautumisaika
10.11.2025 - 14.01.2026
Ilmoittautuminen toteutukselle on käynnissä.
Ajoitus
07.01.2026 - 22.02.2026
Toteutus ei ole vielä alkanut.
Opintopistemäärä
4 op
Lähiosuus
4 op
Toteutustapa
Lähiopetus
Yksikkö
SeAMK Automaatio- ja tietotekniikka
Toimipiste
SeAMK Seinäjoki, Frami
Opetuskielet
englanti
Paikat
0 - 35
Koulutus
Bachelor of Engineering, Automation Engineering
Opettajat
Raine Kauppinen
Ajoitusryhmät
Avoin AMK (Ei koske tutkinto-opiskelijaa) (Koko: 35 . Avoin AMK : 35.)
Ryhmät
AE24
Bachelor of Engineering, Automation Engineering
Pienryhmät
Avoin AMK (Ei koske tutkinto-opiskelijaa)
Opintojakso
AE00CM74

Tavoitteet

Student can implement fundamental data structures and algorithms and compare their properties. Student can use different data structures, such as lists, sets, dictionaries, trees and hashing, and algorithms associated to them. Student can develop applications, which utilizes different kind of data structures and algorithms efficiently.

Sisältö

- Lists, stack, queue
- Dictionaries
- Trees
- Sorting
- Searching
- Hashing
- Principles of algorithm analysis
- Collection classes of C#, Java or C++

Aika ja paikka

The schedules can be found in the timetable at https://lukkarikone.seamk.fi/. Timetables are published for the next six weeks. The first six weeks of autumn are published by Midsummer and the first six weeks of spring by Christmas. Timetables may be subject to changes.

Oppimateriaalit

Information about the materials are in Moodle.

Opetusmenetelmät

The study involves contact teaching and requires attendance at the SEAMK campus. The course is conducted in the Moodle learning environment. The course requires independent work and scheduling.

The recordings of the teaching sessions are not available. The student familiarizes themselves with the material and completes assignments according to the given instructions.

Toteutuksen valinnaiset suoritustavat

No alternative completion methods.

Opiskelijan ajankäyttö ja kuormitus

The workload of the study is designed so that one credit corresponds to an average of 27 hours of student work to achieve the learning objectives. The actual time required varies individually, e.g., due to prior knowledge.

4 cu * 27 h/cu = 108 hours, of which around one third is contact teaching and two thirds independent work.

Arviointikriteerit, tyydyttävä (1)

Student can implement fundamental data structures and algorithms. Student can use lists and dictionaries, and algorithms associated to them.

Arviointikriteerit, hyvä (3)

Student can implement fundamental data structures and algorithms and compare their properties. Student can use different data structures, such as lists, sets, dictionaries, trees and hashing, and algorithms associated to them. Student can develop applications, which utilizes different kind of data structures and algorithms.

Arviointikriteerit, kiitettävä (5)

Student can implement fundamental data structures and algorithms and compare their properties. Student can use different data structures, such as lists, sets, dictionaries, trees and hashing, and algorithms associated to them. Student can develop applications, which utilizes different kind of data structures and algorithms efficiently. Student can analyze the running time of the algorithms.

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