Introduction to artificial intelligence

The aim of this course is to introduce the basics of artificial intelligence based on machine and deep learning. The main concepts covered are:
- Supervised learning, datasets, regression and classification tasks, evaluation metrics
- Neural networks: multilayer perceptron, activation functions, loss functions, stochastic gradient descent
- Convolutional neural networks : image classification, segmentation and object recognition
- Introduction to advanced architectures (Transformers, LLMs)
A project will be carried out aimed at understanding and partially reproducing a method taken from a scientific article, including a technical demonstration.