Artificial Intelligence – Applied Introduction: Concepts, Applications and Challenges

Artificial intelligence (AI) represents one of the digital world domains that is currently the subject of an important development all over the world. This means that citizens are and will be confronted, in their professional and personal lives, with digital products that include some artificial intelligence components.

The objectives of this training are:

• to understand the Artificial Intelligence landscape and the position of deep learning within it
• to discover the main application domains: services to citizens, e-commerce, medicine, entertainment (gaming, music, painting, …), agriculture, accounting, industry 4.0, transportation (cars, trains, planes),
• to play with some accessible artificial intelligence experimenting the various techniques in different application domains
• to understand the social and ethical dimensions of artificial intelligence
• to understand the impact of AI on society and on the job market• to understand through practice all the important notions which constitute the basis of the field of deep learning:
  – neural network, weight, activation function, batch, bias, cost function, dropout, epoch, forward/backward propagation, gradient descent, hidden layer, parameters, hyper-parameters, input, output, learning rate, dataset, data augmentation, training, validation, test datasets, architecture, ANN, CNN, RNN, GAN, Transformers

• to understand through practice the main deep learning techniques such as:
  – supervised, semi-supervised, unsupervised
• to get an intuitive comprehension of the main mathematical tools which are:
  – calculus (functions,…), algebra (matrices,…), probabilities