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Generative AI as a Tool for Designers (5 cr)

Code: KD00FM12-3001

General information


Enrollment

01.10.2023 - 30.04.2024

Timing

01.10.2023 - 31.07.2024

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Unit

School of Media, Design and Conservation

Campus

Hämeentie 135

Teaching languages

  • Finnish

Seats

0 - 30

Degree programmes

  • Design

Teachers

  • Markus Norrena

Teacher in charge

Markus Norrena

Objective

The student knows different generative artificial intelligence tools and knows how to use them as part of the work processes of a digital designer. The student can think about the differences between different tools and their possibilities. The student knows how to think about these tools and their effects on the industry and society more broadly.

Content

The course offers an understanding of how artificial intelligence can be used as part of the work processes of a digital designer currently and in the near future. The course is open to everyone and you don't need prior knowledge of the work of a digital designer, but a general interest in or understanding of the field helps.

During the course, we both practice the use of generative artificial intelligence tools and we consider how artificial intelligence has changed and is still changing both society and the activities of the creative industry. The course starts from the basics and does not require previous use of artificial intelligence tools.

The course is part of Metropolia's Digital Design teaching, and that is why we approach the topic especially from the perspective of a digital designer, although we partially look at artificial intelligence as part of the creative field more broadly.

You can complete the course at your own pace, and the course is evaluated on a pass or fail scale at the end.

Location and time

In Moodle at your own pace, regardless of location. Address: https://moodle.metropolia.fi/course/view.php?id=31

Materials

The course contains constantly updated teaching material because the topic is so new that it is updated all the time. There is no other recommended literature.

Teaching methods

Reading material, independent writing, trying out different tools, peer feedback and learning tests. Although the studying is done independently, we also hope to learn together through assignments for others to comment on.

Exam schedules

We progress at our own pace and tests can be renewed at own pace, as long as the course material is maintained.

Completion alternatives

Cannot be completed in any other way.

Student workload

The course is 5 credits long and also requires the same amount of work. The course has a lot to read, try and think about, as well as several writing, experimenting and reflection tasks. Be prepared that learning takes time.

Content scheduling

The content/modules of the course are as follows:

1. Katsaus tekoälyn tilaan ja työkaluihin
2. Digitaalisen Muotoilijan työ lyhyesti
3. Kielen ja tekstin tekoälytyökalut
4. Visuaaliset tekoälytyökalut
5. Muita generatiivisia tekoälyapuvälineitä
6. Edellisten yhdistäminen, luo verkkosivu tekoälytyökaluin
7. Tekoälyn eettiset ja yhteiskunnalliset näkökulmat
8. Tekoälyn tulevaisuudennäkymiä

Please note that some of the sections are significantly longer than others (e.g. sections 1, 3 and 4 and the task of section 6 are quite extensive and form the central content of the course).

Since the course material is constantly updated, the above division may also change slightly if necessary.

Further information

The course consists of eight actual parts. Each part first has some pdf material that should be carefully reviewed. The material itself has some small tasks that I encourage you to do. After the material, there are also Moodle assignments in each section. These Moodle assignments are mandatory for passing the course.

Please also note that the contents are updated all the time and some PDFs may be updated to a newer version during the course.

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, approved/failed

Hyväksytty: opiskelija palauttaa kaikki kurssilla vaadittavat tehtävät
Hylätty: opiskelija ei palauta kaikkia kurssilla vaadittuja tehtäviä

Assessment methods and criteria

Pass/fail

Further information

You can complete the course at your own pace, and the course is evaluated on a pass or fail scale at the end.