Interactive Technology and AI (5cr)
Code: MS00CR81-3001
General information
- Enrollment
- 01.08.2024 - 16.09.2024
- Registration for the implementation has ended.
- Timing
- 16.09.2024 - 31.12.2024
- Implementation has ended.
- Number of ECTS credits allocated
- 5 cr
- Local portion
- 5 cr
- Mode of delivery
- Contact learning
- Unit
- Engineering and Business
- Teaching languages
- English
- Degree programmes
- Master of Engineering, Interactive Technologies
- Master of Business Administration, Interactive Technologies
- Teachers
- Timo Haavisto
- Werner Ravyse
- Course
- MS00CR81
Realization has 2 reservations. Total duration of reservations is 7 h 15 min.
Time | Topic | Location |
---|---|---|
Mon 16.09.2024 time 12:30 - 16:30 (4 h 0 min) |
Interactive Technology and AI MS00CR81-3001 |
Online
|
Mon 07.10.2024 time 08:15 - 11:30 (3 h 15 min) |
Interactive Technology and AI MS00CR81-3001 |
Online
|
Evaluation scale
H-5
Objective
Upon completing the Interactive Technology and AI course, students will be able to:
- Calculate and interpret AI evaluation metrics.
- Propose and integrate a relevant and feasible AI solution into an interactive technology application.
- Find and critically apply relevant academic research toward solving an engineering challenge.
- Design and implement an experiment to test AI interventions for or stemming from interactive technology applications.
Content
At the start of the course, students will go through a groundwork phase where they will attend a series of lectures on the latest AI techniques and what they mean for the interactive technology industry. These lectures will also contain material on how to critically evaluate AI solutions, both quantitatively and for practical feasibility.
After the groundwork phase, students will enter an individual conceptualisation phase. During this phase, students will be presented with a real-world problem from one of the Futuristic and Interactive Technologies research group’s RDI projects. Students are expected to consult academic literature and other reputable sources to conceptualise an AI implementation for the problem they were presented.
Upon completing the conceptualisation phase, students will commence a practical phase where they will be placed into a team to either implement the output of their conceptualisation phase or scientifically test an existing AI application.