This new course focuses on using the Python programming language to interact with the various interfaces (APIs) used in artificial intelligence.
Several basic concepts will be covered in order to demystify AI: supervised and unsupervised learning, datasets, model training, performance evaluation, etc.
The fundamental concepts of the Python programming language will be presented, including data types and structures, loops, conditions, functions, syntax and libraries. In addition, the most commonly used libraries in machine learning will be presented, as well as commercial APIs from OpenAI, Anthropic, Midjourney, Stable Diffusion, etc. Algorithm training concepts will be covered. Guided coding sessions are planned to integrate what has been learned. Demonstration of interactive machine learning (IML) with Touch Designer. Finally, topical issues will be addressed to stimulate critical thinking.
Detailed Program
Saturday, February 22nd
Morning
Explanation of the basic concepts of machine learning, supervised and unsupervised, datasets, model training and performance evaluation.
Afternoon
Presentation of the fundamental concepts of the Python programming language used for machine learning, including data structures, loops, conditions and functions. Presentation of the most commonly used libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, and TensorFlow or PyTorch, as well as the commercial APIs of OpenAI, Anthropic, Midjourney, Stable Diffusion. A short API call session to integrate what has been learnt.
The artist Sofian Audry will be a guest speaker to talk about his own explorations in AI to complement learning.
Sunday, February 23rd
Morning
Review of training concepts (and how to improve results). Guided coding session using what has been learned.
Afternoon
Demonstration ofInteractive Machine Learning (IML) with Touch Designer. Guided coding session, with help and comments from the trainer. Presentation of current issues and critical reflections on machine learning technologies.
Maxime-Alexandre Gosselin
Photo credit :
Life by Selena
Sofian Audry
Sofian Audry is an artist, scholar, Professor of Interactive Media within the School of Media at the University of Quebec in Montreal (UQAM), Co-Director of the mXlab studio-lab for Beyond-Human Media Creation, and Co-Director of the Hexagram Network for Research-Creation in Art, Culture and Technology.
Their work explores the behavior of hybrid agents at the frontier of art, artificial intelligence, and artificial life, through artworks and writings. Audry’s book Art in the Age of Machine Learning examines machine learning art and its practice in art and music (MIT Press, 2021). Their artistic practice branches through multiple forms including robotics, installations, bio-art, and electronic literature.
Audry studied computer science and mathematics (BSc, 2001), machine learning (MSc, 2003), and communication (interactive media) (MA, 2010) before completing a PhD in Humanities from Concordia University (2016). In 2017, they were a Postdoctoral Fellow at the Massachusetts Institute of Technology, and between 2017 and 2019, held Assistant Professor positions at the University of Maine and at Clarkson University. Sofian is an honorary member of artist-run center Perte de Signal (Montréal, Canada) which they led as president of the board in 2009-2017, and is actively involved in many open source softwares for new media.
Sofian Audry’s work and research have been shown at major international events and venues such as Ars Electronica, Barbican, Centre Pompidou, Club Transmediale, Dutch Design Week, Festival Elektra, International Digital Arts Biennale, International Symposium on Electronic Art, LABoral, La Gaîté Lyrique, Marrakech Biennale, Nuit Blanche Paris, Society for Arts and Technology, V2 Institute for Unstable Media, Muffathalle Munich and the Vitra Design Museum.
