Data analytics and artificial intelligence (5 op)
Toteutuksen tunnus: YA00CF18-3001
Toteutuksen perustiedot
Ilmoittautumisaika
01.08.2024 - 31.12.2024
Ajoitus
01.01.2025 - 31.07.2025
Opintopistemäärä
5 op
Virtuaaliosuus
5 op
TKI-osuus
3 op
Toteutustapa
Etäopetus
Yksikkö
KAMK Master School
Opetuskielet
- Suomi
Koulutus
- Master’s Degree in Game Business Management
Opettaja
- Himat Shah
Ryhmät
-
MGB23SMGB23S
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MGBE23SMGBE23S
- 16.01.2025 16:00 - 18:00, Opening lecture_Data analytics and artificial intelligence YA00CF18-3001
- 27.02.2025 16:00 - 16:30, Q&A_Data analytics and artificial intelligence YA00CF18-3001
- 19.03.2025 16:00 - 16:30, Q&A_Data analytics and artificial intelligence YA00CF18-3001
- 02.04.2025 16:00 - 16:30, Q&A_Data analytics and artificial intelligence YA00CF18-3001
- 07.05.2025 16:00 - 16:30, Q&A_Data analytics and artificial intelligence YA00CF18-3001
Tavoitteet
After completing the course, the student becomes aware of the importance of knowledge-based management and knows how to apply knowledge and data in the development of business and organizational operations. The student knows the basics of artificial intelligence and data analytics. The student understands what kind of challenges and solutions are suitable for data analytics, and how data analytics can be used to improve the predictability of business and organizational operations and increase productivity. The student knows the steps of preparing a company's data strategy.
Sisältö
The course consists of two parts: Basics of Artificial Intelligence (2 ECTS) and Data Analytics and Business Intelligence (3 ECTS). The course is completed ndependently online, and it does not include time-bound contact teaching.
The main content areas of the course are
- Knowledge-based management
- Basics of artificial intelligence
- Basics of data analytics
- Utilization of artificial intelligence, data analytics and Business Intelligence in business
- Data strategy components and preparation
Arviointiasteikko
0 - 5
Arviointikriteeri, hyväksytty/hylätty
In the course, either numerical evaluation (0-5) or pass/fail evaluation is applied. The evaluation scale is announced in the beginning of the course. Completion of the course requires the successful completion of both parts, basics of artificial intelligence (2 ECTS) and data analytics and BI (3 ECTS).
Fundamentals of artificial intelligence (2 ECTS) section has been successfully completed when at least 90% of the tasks have been completed and the achieved score is at least 50% of the total score of the course.
Completing the data analytics and BI (3 ECTS) section requires passing all short exams and practical assignment.
Esitietovaatimukset
No prerequisites
Lisätiedot
The evaluation scale of the course is either numerical (0-5) or two-step (Pass/Fail). The evaluation scale is announced in the beginning of the course.