Teaching Fundamentals of Neural Networks with MATLAB

In this webinar attendees will explore how to utilize ‘Fundamentals of Neural Networks’ courseware. This material was developed by Prof. Potočnik in collaboration with the MathWorks Academia Team.

AI is generally recognized as a key technology broadly adopted in many application domains. Recently, the permeation of AI in different science disciplines has become predominant. Many universities started to design new courses aimed at teaching young students the fundamental theory of AI (e.g., neural network) so that students can effectively address the main challenges when entering the job market and/or contributing to research advancements. The material developed in this project is aimed at addressing the need from instructors to have ready-to-use content to teach the fundamental theory of AI. The content exploits the latest MathWorks teaching tools (e.g., online trainings, dedicated Toolboxes, Apps, and the online tools of the CWL) which can be used to explain the basics of AI and allow a quick understanding of AI with low-code solutions.

This teaching package contains modular contents for the introduction of the fundamentals of Neural Networks. The package consists of a series of MATLAB Live Scripts with complementary PowerPoint presentations. The package is intended to gradually guide the students toward basic concepts in neural networks through general demonstrations applicable to every field, spanning from science to engineering. The materials also include a classical engineering problem, namely industrial diagnostics of compressor connection rod defects.

The contents are mainly addressed towards undergraduate courses. However, the modular structure allows further integration within other (postgraduate) AI-based courses. Course application areas include Neural Networks, Deep Learning, Machine Learning, Industrial diagnostics and Condition Monitoring, and Autonomous Systems.