Università Roma Tre

Introduction to Artificial Intelligence
Numerical modeling and use of computers in scientific computing
Artificial neural networks: the multilayer perceptron (MLP)
Interpolation and approximation with neural networks (linear and non-linear regression), graphic example also in 3D
Supervised training: backpropagation algorithm for calculating the gradient of the error function of an MLP
Introduction to optimization: training algorithms
Convolutional Neural Networks (CNN)
Recursive Neural Networks (RNN)
Unsupervised training
Reinforcement training
Generative neural networks
Genetic algorithms
Swarm intelligence
Development of source codes in C/C++ as libraries for Matlab and Python

Application examples:
Simulation of a solar cell with neural networks
Neural networks for solar panel optimization
Neural solarimeter
Resolution of thermal circuits
Calculation of the parameters of the static Jiles – Atherton model
Calculation of the parameters of the one-diode model of a solar cell

Dive into deep learning
https://d2l.ai/