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AI Applications (5cr)

Code: 5Y00HC66-3001

General information


Enrolment period
02.07.2025 - 15.09.2025
Registration for the implementation has ended.
Timing
25.08.2025 - 21.12.2025
Implementation is running.
Credits
5 cr
Mode of delivery
Contact learning
Unit
MD in Data Expertise and Artificial Intelligence
Campus
TAMK Main Campus
Teaching languages
Finnish
Degree programmes
Master's Degree Programme in Data Expertise and Artificial Intelligence
Teachers
Teemu Heinimäki
Person in charge
Jere Käpyaho
Tags
CONTACT
Course
5Y00HC66

Objectives (course unit)

The student is able to implement various applications utilizing artificial intelligence and knows how to use data as part of an artificial intelligence application. The student knows different artificial intelligence application techniques and methods and is able to choose the most suitable one for different applications.

Content (course unit)

Designing and implementing an artificial intelligence application using a programming language, processing data as part of an artificial intelligence application, teaching and testing artificial intelligence models, and evaluating results.

Assessment criteria, satisfactory (1-2) (course unit)

The student knows how to implement an artificial intelligence application and knows how to use the data as part of an artificial intelligence application. The student knows some application technology and / or method of artificial intelligence.

Assessment criteria, good (3-4) (course unit)

The student is able to implement various applications utilizing artificial intelligence and knows how to use data as part of an artificial intelligence application. The student is familiar with some artificial intelligence application techniques and methods and can use some of them.

Assessment criteria, excellent (5) (course unit)

The student knows how to implement various applications using artificial intelligence and knows how to use data as part of an artificial intelligence application. The student is versatile in different artificial intelligence application techniques and methods and is able to choose the most suitable one for different applications.

Location and time

Lähisessioita toisessa periodissa tilassa A3-24. Aloitus 9.10.2025 klo 16.30. Ajantasaisia aikataulutietoja ylläpidetään Moodlessa.

Exam schedules

Lähtökohtaisesti ei tenttiä.

Assessment methods and criteria

Arviointi perustuu opintojakson aikana suoritettuihin kurssiaktiviteetteihin (tehtävät, esitykset, projektit yms.) ja niistä kertyviin pisteisiin. Arvosana määräytyy kerättyjen pisteiden prosenttiosuudesta suurimpaan mahdolliseen kokonaispistemäärään nähden alustavasti seuraavasti:
[0 % – 50 %[: 0
[50 % – 60 %[: 1
[60 % – 70 %[: 2
[70 % – 80 %[: 3
[80 % – 90 %[: 4
[90 % – 100 %]: 5
Joidenkin aktiviteettien hyväksytty suoritus voidaan edellyttää, jotta opintojakson voi läpäistä – esim. itse- ja vertaisarviointeja voidaan vaatia.

Assessment scale

0-5

Teaching methods

Luennot/harjoitukset, projektit, esitykset, verkko-opetus, itseopiskelu, ongelmalähtöinen oppiminen, mahdollisesti ryhmätyö, itse-/vertaisarviointi

Learning materials

Ilmoitetaan opintojakson alussa. Lähtökohtaisesti ei pakollista kurssikirjaa.

Student workload

Suunniteltu keskimääräinen opiskelijan ajankäyttö n. 135 h, jakautuu tasaisesti opintojakson kestolle.

Completion alternatives

(Tarvittaessa yhteys opettajaan erityisjärjestelyjen osalta.)

Practical training and working life cooperation

Ei takeita, mutta tutkitaan mahdollisuutta vierailuluentoon.

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