AI in Business (3 ECTS)
Code: TX00GL11-3001
General information
- Enrollment
- 05.05.2025 - 30.07.2025
-
Enrollment is ongoing
Enroll to the implementation in OMA
- Timing
- 04.08.2025 - 08.08.2025
- The implementation has not yet started.
- Number of ECTS credits allocated
- 3 ECTS
- Mode of delivery
- On-campus
- Unit
- School of ICT and Industrial Management
- Campus
- Leiritie 1
- Teaching languages
- English
- Seats
- 0 - 20
- Teachers
- ICT Exchange Teacher
- Course
- TX00GL11
Implementation has 5 reservations. Total duration of reservations is 20 h 0 min.
| Time | Topic | Location |
|---|---|---|
|
Mon 04.08.2025 time 13:00 - 17:00 (4 h 0 min) |
AI in Business TX00GL11-3001 |
MMC240
Oppimistila
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Tue 05.08.2025 time 13:00 - 17:00 (4 h 0 min) |
AI in Business TX00GL11-3001 |
MMC240
Oppimistila
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Wed 06.08.2025 time 13:00 - 17:00 (4 h 0 min) |
AI in Business TX00GL11-3001 |
MMC240
Oppimistila
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Thu 07.08.2025 time 13:00 - 17:00 (4 h 0 min) |
AI in Business TX00GL11-3001 |
MMC240
Oppimistila
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Fri 08.08.2025 time 13:00 - 17:00 (4 h 0 min) |
AI in Business TX00GL11-3001 |
MMC240
Oppimistila
|
Learning outcomes
By the end of the course, students will be able to:
• Analyze business processes to identify AI opportunities
• Develop strategic plans for AI integration
• Design and prototype AI-driven solutions
• Communicate AI strategies effectively in a business context
Content
This course explores the strategic application of Artificial Intelligence (AI) within business contexts. Rather than focusing solely on off-the-shelf productivity tools, students will learn to embed AI solutions into business processes to drive real value and innovation.
Through a mix of theory and hands-on group work, students will identify critical business challenges, design tailored AI solutions, and develop implementation strategies. The emphasis lies on aligning AI initiatives with broader business goals—transforming AI from a buzzword into a practical asset.
Students will also learn how to effectively leverage Generative AI tools (e.g., ChatGPT) for opportunity discovery, strategy development, and prototyping.
By the end of the course, students will have created and presented a working prototype—such as a customized chatbot or low-code ML model—targeted at solving a real-world business problem for an organization of their choice.
Assessment methods and criteria
Group presentation of AI strategy and solution prototype
Individual grades reflect participation and engagement
Evaluation scale
Hyväksytty/Hylätty