Data Analytics and Basics of Artificial Intelligence (5 cr)

Objectives (course unit)

The student knows the basics of data analysis and the most important methods in the Python programming language. The student knows how to process, analyze and visualize data. The student knows the basics of artificial intelligence, the most important concepts and knows different applications.

Content (course unit)

Fundamentals of data analysis and key methods in Python programming language. Processing, analyzing and visualizing data. The basics of artificial intelligence, the most important concepts and different applications.

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

The student is able to process data, analyze and make visualizations. The student knows the basics of artificial intelligence and the most important concepts.

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

The student is able to process data, analyze and make visualizations. The student knows the basics of artificial intelligence, the most important concepts and can create artificial intelligence applications based on examples.

Assessment criteria, excellent (5) (course unit)

The student is able to handle, analyze and visualize data in a versatile way. The student knows well the basics of artificial intelligence, the most important concepts and knows how to create artificial intelligence applications.

Exam schedules

ei tenttiä

Assessment methods and criteria

Arvosana koostuu viikkoharjoituksista ja kahdesta oppimistehtävästä. Toinen oppimistehtävä on data-analyysiin liittyvä ja toinen koneoppimiseen / tekoälyyn.

Viikkotehtävistä voi saada 0-1 pisteen ja oppimistehtävistä kustakin 0-2. Pisteet lasketaan yhteen ja summasta muodostuu arvosana. Viikkotehtäviä tulee tehdä min. 80 %, jotta yhden arvosanapisteen voi saada.

Pisteiden tarkempi kuvaus moodlessa.

Assessment scale

0-5

Learning materials

moodlessa