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AI Applications (5 cr)

Code: 5Y00FE88-3004

General information


Enrolment period
04.05.2024 - 20.10.2024
Registration for the implementation has ended.
Timing
26.08.2024 - 22.12.2024
Implementation has ended.
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
Jere Käpyaho
Person in charge
Jere Käpyaho
Course
5Y00FE88

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.

Exam schedules

ei tenttiä

Assessment methods and criteria

1 - esimerkin testailua ja raportti
2 - oma case omalla datalla, testailua ja raportti
3 - oma case kahden erilaisen mallin opettaminen, testailua ja raportti
4 - oma case, kolmen erilaisen mallin opettaminen, tulosten vertailu keskenään ja pohdinta siitä, mikä menetelmä antoi parhaan tuloksen, metriikoiden ja tunnuslukujen käyttöä ja niiden pohdintaa, testailua ja raportti
+1 esitys

Assessment scale

0-5

Assessment criteria - fail (0) (Not in use, Look at the Assessment criteria above)

ei palautusta eikä esitystä

Assessment criteria - satisfactory (1-2) (Not in use, Look at the Assessment criteria above)

Opiskelija osaa toteuttaa ohjatusti tekoälyä hyödyntävän sovelluksen ja tietää, miten dataa käytetään osana tekoälysovellusta. Opiskelija tuntee jonkin tekoälyn sovellustekniikan ja/tai menetelmän.

Assessment criteria - good (3-4) (Not in use, Look at the Assessment criteria above)

Opiskelija osaa toteuttaa erilaisia tekoälyä hyödyntäviä sovelluksia ja tietää, miten dataa käytetään osana tekoälysovellusta. Opiskelija tuntee joitakin tekoälyn sovellustekniikoita ja menetelmiä sekä osaa käyttää niistä jotakin.

Assessment criteria - excellent (5) (Not in use, Look at the Assessment criteria above)

Opiskelija osaa toteuttaa monipuolisesti erilaisia tekoälyä hyödyntäviä sovelluksia ja tietää hyvin, miten dataa käytetään osana tekoälysovellusta. Opiskelija tuntee monipuolisesti erilaisia tekoälyn sovellustekniikoita ja menetelmiä sekä osaa valita niistä sopivimman eri käyttötarkoitukseen.

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