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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
Changes to reservations may be possible.

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.

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