Genetic Algorithms & Neural Networks: Java, AI

Course OverviewExplore the cutting-edge of artificial intelligence with our detailed course on Genetic Algorithms and Neural Networks. This course is structured to take you from a theoretical understanding of complex algorithms to direct, hands-on application through a series of engaging activities and real-world problems. Perfect for those looking to deepen their AI expertise, the course covers everything from basic structures and functions to advanced applications in games and pattern recognition.

Learning ObjectivesBy the end of this course, students will:Understand the principles and components of Genetic Algorithms, including selection, crossover, and mutation processes. Gain practical experience with Genetic Algorithms by solving problems like the Traveling Salesman and function optimization. Learn the basics of Neural Networks and apply them to real-world tasks such as digit recognition.

Develop an understanding of neuro-evolution techniques by creating a self-learning "Snake Game". Critically analyze the advantages and limitations of these AI techniques and their applications. Target AudienceThis course is designed for:Students and professionals interested in advanced AI technologies.

Data scientists and engineers looking to add sophisticated algorithmic methods to their toolkits. Course ModulesTheoryGenetic Algorithm Overview: Introduction and history. Fundamentals: Basic structure, parent selection, crossover, mutation, and survivor selection.