Artificial Neural networks currently belong to the most popular and widely used algorithms for artificial intelligence and machine learning applications. This course addresses methods of deep learning using the Python programming language. It introduces the basic models, learning algorithms, and some applications of neural networks in practice. Attendees will learn how to work with the TensorFlow library, which is currently the most popular library for designing, training and testing deep learning programs. 

Topics covered:
1.    Basic principles of artificial intelligence, machine learning and neural networks
2.    TensorFlow: introduction and installation
3.    TensorFlow deployment: models, activation functions, loss functions, layers, initializers, metrics, callbacks, optimizers etc.
4.    Practical TensorFlow examples: regression methods, text and image classification (convolutional neural networks)
5.    TensorBoard: model design, selection and evaluation