Artificial Intelligence (5 op)

Arviointiasteikko

0-5

Tavoitteet

The student understands the purpose of artificial intelligence and knows the importance and possibilities of data. The student understands the importance of data quality and the ethics of artificial intelligence. The student will know the steps of data analytics/machine learning/deep learning processes. The student has knowledge and skills to plan a data strategy.

Course competences
EUYKN EUR-ACE: Knowledge and Understanding, Master's Degree

EUYCT EUR-ACE: Communication and Team-working, Master's Degree

EUYLL EUR-ACE: Lifelong Learning, Master's Degree

Sisältö

The key topics of the course are:
The possibilities of data
Ethics of Artificial Intelligence (AI)
The importance of data quality
Methodology of Data analytics (DA) and AI
DA and AI project process and management
Data strategy
Open source tools to DA, ML and AI

Aika ja paikka

Kontaktiopetus perjantaisin klo 14-20 ja lauantaisin klo 9-15.
Opetus on IT-Dynamolla, Piippukatu 2, 40100 Jyväskylä.

Oppimateriaalit

Määrittellään ensimmäisellä luennolla.

Opetusmenetelmät

Kontaksiopetus 2 viikonloppua lukukauden aikana.
Kontaktipäivien välissä harjoitustehtäviä ja etäopetusta.
Harjoitustyö omaan tilanteeseen liittyvästä aiheesta.

Harjoittelu- ja työelämäyhteistyö

It is advisable that the students use their own work environment as an object of study and as a data source.
Possible guest lecturers from companies.

Opiskelijan ajankäyttö ja kuormitus

5 ECTS credits equals about 135 hours of study work.
Contact instruction: 24 hours
Exercises: 48 hours
Study project: 63 hours

Arviointikriteerit, tyydyttävä (1)

**Assessment criteria, sufficient 1, satisfactory 2
Sufficient 1: Student has sufficient knowledge of data analytics and artificial intelligence and the possibilities of data. Student is able to form a partially comprehensive data strategy and describe the DA/AI process. In addition, student understands the restrictions of GDPR legislation and regulations and the ethical aspects affecting the operations of actors at a sufficient level.

Satisfactory 2: Student has satisfactory knowledge of data analytics and artificial intelligence and the possibilities of data. Student is able to form a partially comprehensive data strategy and describe the DA/AI process. In addition, student understands the restrictions of GDPR legislation and regulations and the ethical aspects affecting the operations of actors at a satisfactory level.

Arviointikriteerit, hyvä (3)

Good 3: Student has good knowledge of data analytics and artificial intelligence and the possibilities of data. Student is able to form a partially comprehensive data strategy and describe the DA/AI process. In addition, student understands the restrictions of GDPR legislation and regulations and the ethical aspects affecting the operations of actors well.

Very Good 4: Student has very good knowledge of data analytics and artificial intelligence and the possibilities of data. Student is able to form a comprehensive data strategy and describe the DA/AI process. In addition, student understands the restrictions of GDPR legislation and regulations and the ethical aspects affecting the operations of actors very well.

Arviointikriteerit, kiitettävä (5)

Excellent 5: Student has excellent knowledge of data analytics and artificial intelligence and the possibilities of data. Student is able to form a comprehensive data strategy and describe the DA/AI process. In addition, student understands excellently the restrictions of GDPR legislation and regulations and the ethical aspects affecting the operations of actors.

Lisätiedot

Avoin AMK polkuopiskelijat: 5 paikkaa