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, May 24th

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.

Sunday, May 25th

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.