Syllabus

OSAAMISTAVOITTEET

On successful completion of this course, students will be able to:

• Understand how common AI and machine learning algorithms & tools work on an intuitive, non-mathematical level, based on visualizations and practical experiments.
• Understand what the tools can be used for in context of art, media, and design.
• Process and/or generate images, audio, and/or text using AI and machine learning tools such as Colab Python Notebooks and Unity Machine Learning Agents
• Continue learning and experimentation independently

For more details, see the full syllabus, code examples, and exercises at https://github.com/PerttuHamalainen/MediaAI/tree/master/Lessons (updated continuously), and follow the course Twitter feed: https://twitter.com/aaltomediaai.

Laajuus: 3

Aikataulu: 11.01.2023 - 17.02.2023

Vastuuopettaja (voimassa koko opetussuunnitelmakauden):

Vastuuopettaja (koskee tätä kurssikertaa): Perttu Hämäläinen

Kurssin yhteystiedot (koskee tätä kurssikertaa):

Kurssin CEFR-taso (voimassa koko opetussuunnitelmakauden):

Opetuskieli ja suorituskielet (koskee tätä kurssikertaa):

Teaching language: Finnish. Languages of study attainment: English

SISÄLTÖ, ARVIOINTI JA KUORMITTAVUUS

Sisältö

• voimassa koko opetussuunnitelmakauden:

  This is a hands-on, project-based crash course on deep learning and other AI techniques for people with only few technical prerequisites:

  • Basic programming skills (e.g., some python, processing, or Unity C#)
  • Basic high-school math. We focus on visual explanations that are enough to understand why and how various AI methods work.

  The focus is on media processing and games, which makes this particularly suitable for artists and designers.

  The lessons and materials comprise three parts:

  • Lectures
  • Software examples
  • Exercises that require you to modify the sofware examples to test your learning. The exercises provide both easy and advanced exercises to cater for different skill levels. Model solutions are provided for the easier ones, but some of the advanced exercises are left to the students and can also work as final project topics.

  Full syllabus and materials (updated for each run of the course):
  https://github.com/PerttuHamalainen/MediaAI
  Links and resources (updated continuously):
  https://twitter.com/aaltomediaai

Toteutus, työmuodot ja arvosteluperusteet

• voimassa koko opetussuunnitelmakauden:

  Completing a final project.

Työmäärä toteutustavoittain

• voimassa koko opetussuunnitelmakauden:

  Lectures, programming exercises, and a final project. The final project can focus on either applying or creating some AI or machine learning approach for creative use.

PERUSTIETOJA

Korvaavuudet

• voimassa koko opetussuunnitelmakauden:

  Korvaavuudet

Esitiedot

• voimassa koko opetussuunnitelmakauden:

  Esitiedot

LISÄTIETOJA

Lisätietoja

• voimassa koko opetussuunnitelmakauden:

  Teaching Language : English

  Teaching Period : 2022-2023 Spring III
  2023-2024 Spring III

Description