Data-analysis, Data Visualization and Artificial IntelligenceLaajuus (5 cr)
Code: NY00EK76
Credits
5 op
Objectives
The student knows the basics of data analysis and the most important methods. The student knows how to process, analyze and visualize data. The student knows the basics of artificial intelligence, the most important concepts and is able to interpret the results and know the limitations and possibilities of the methods.
Content
The basics of data analysis and the main methods. Processing, analyzing and visualizing data. Basics of Artificial Intelligence, key concepts and methodology evaluation.
Assessment criteria, satisfactory (1-2)
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)
The student is able to process data, analyze and make visualizations. The student knows the basics of artificial intelligence, the most important concepts and knows the limitations and possibilities of methods.
Assessment criteria, excellent (5)
The student is able to handle data in a versatile way, analyze and visualize. Students are familiar with the basics of artificial intelligence, the most important concepts and are able to interpret the results and know the limitations and possibilities of the methods.
Enrolment period
05.06.2024 - 30.08.2024
Timing
05.09.2024 - 05.10.2024
Credits
5 op
Virtual portion
5 op
Mode of delivery
Distance learning
Campus
TAMK Main Campus
Teaching languages
- Finnish
Seats
0 - 40
Teachers
- Esa Parkkila
Person in charge
Ossi Nykänen
Groups
-
24YAMKYlempi AMK, yhteiset opinnot
Objectives (course unit)
The student knows the basics of data analysis and the most important methods. The student knows how to process, analyze and visualize data. The student knows the basics of artificial intelligence, the most important concepts and is able to interpret the results and know the limitations and possibilities of the methods.
Content (course unit)
The basics of data analysis and the main methods. Processing, analyzing and visualizing data. Basics of Artificial Intelligence, key concepts and methodology evaluation.
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 knows the limitations and possibilities of methods.
Assessment criteria, excellent (5) (course unit)
The student is able to handle data in a versatile way, analyze and visualize. Students are familiar with the basics of artificial intelligence, the most important concepts and are able to interpret the results and know the limitations and possibilities of the methods.
Assessment scale
0-5
Enrolment period
10.08.2023 - 08.09.2023
Timing
09.09.2023 - 06.10.2023
Credits
5 op
Virtual portion
5 op
Mode of delivery
Distance learning
Campus
TAMK Main Campus
Teaching languages
- Finnish
Seats
0 - 40
Teachers
- Ossi Nykänen
Groups
-
23YAMK
Objectives (course unit)
The student knows the basics of data analysis and the most important methods. The student knows how to process, analyze and visualize data. The student knows the basics of artificial intelligence, the most important concepts and is able to interpret the results and know the limitations and possibilities of the methods.
Content (course unit)
The basics of data analysis and the main methods. Processing, analyzing and visualizing data. Basics of Artificial Intelligence, key concepts and methodology evaluation.
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 knows the limitations and possibilities of methods.
Assessment criteria, excellent (5) (course unit)
The student is able to handle data in a versatile way, analyze and visualize. Students are familiar with the basics of artificial intelligence, the most important concepts and are able to interpret the results and know the limitations and possibilities of the methods.
Assessment scale
0-5
Enrolment period
16.05.2022 - 31.08.2022
Timing
08.09.2022 - 06.10.2022
Credits
5 op
Mode of delivery
Contact teaching
Teaching languages
- Finnish
Seats
0 - 40
Teachers
- Ossi Nykänen
Groups
-
22YAMKYlempi amk, yhteiset opinnot
Objectives (course unit)
The student knows the basics of data analysis and the most important methods. The student knows how to process, analyze and visualize data. The student knows the basics of artificial intelligence, the most important concepts and is able to interpret the results and know the limitations and possibilities of the methods.
Content (course unit)
The basics of data analysis and the main methods. Processing, analyzing and visualizing data. Basics of Artificial Intelligence, key concepts and methodology evaluation.
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 knows the limitations and possibilities of methods.
Assessment criteria, excellent (5) (course unit)
The student is able to handle data in a versatile way, analyze and visualize. Students are familiar with the basics of artificial intelligence, the most important concepts and are able to interpret the results and know the limitations and possibilities of the methods.
Assessment scale
0-5