Please note! Course description is confirmed for two academic years (1.8.2018-31.7.2020), which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

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

  • Understand how common AI 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 Tensorflow, PyTorch, Jupyter Notebooks, 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

Credits: 3

Schedule: 02.02.2021 - 19.02.2021

Teacher in charge (valid 01.08.2020-31.07.2022): Perttu Hämäläinen

Teacher in charge (applies in this implementation): Perttu Hämäläinen

Contact information for the course (applies in this implementation):

CEFR level (applies in this implementation):

Language of instruction and studies (valid 01.08.2020-31.07.2022):

Teaching language: English

Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content
  • Valid 01.08.2020-31.07.2022:

    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. We always try to 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

     

Assessment Methods and Criteria
  • Valid 01.08.2020-31.07.2022:

    This is a pass/fail course, as students come from highly varying backgrounds and considerable freedom is given for selecting the final project topics. Thus, it is challenging to establish objective criteria for numerical grading.

    Extra credits can be gained based on time spent on the final project.

Workload
  • Valid 01.08.2020-31.07.2022:

    In class: Lectures, programming and media generation/processing exercises (36h).

    Individually: final project. Note: if you do an ambitious project, it is possible to gain more credits using the Game Study Project course code.

DETAILS

Study Material
  • Valid 01.08.2020-31.07.2022:

    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

     

     

Substitutes for Courses
  • Valid 01.08.2020-31.07.2022:

    Substitutes course with same name (DOM-E5129) but amount of credits changes

Prerequisites
  • Valid 01.08.2020-31.07.2022:

    Mandatory: DOM-E5092 Software Studies for Game Designers(V) (3 cr) or basic programming experience.

    Knowledge of linear algebra, probability, and statistics helps but is not mandatory. Recommended prerequisites for sound students: (DOM-E5067) Sound and Music Interaction, (DOM-E5043) Physical Interaction Design, (DOM-E5074) Composing With Data Flow Programming. Recommended prerequisites for game students: DOM-E5080 Game Design.

     

FURTHER INFORMATION

Description

Registration and further information