This tutorial introduces concepts and methods related to artificial intelligence (AI), focusing on the development of machine learning applications, which are a fundamental aspect of AI. It is designed for students in the Faculty of Computer Science and Applied Mathematics. Additionally, it can serve as a valuable resource for both novice programmers and experienced professionals who aim to create machine learning models using the Python programming language. The educational material in the manual is essential for understanding neural networks, their structure, training methods, and implementations.

It describes the key methods and tools necessary for developing neural networks. The manual includes a variety of practical examples that enable students to apply their programming knowledge in Python.

It presents program codes that illustrate how neural networks are structured and work. Additionally, the examples incorporate the primary classes from popular artificial intelligence libraries such as scikit-learn, Keras, and TensorFlow, providing students with the opportunity to utilize modern software tools effectively.