Foundations of Neural Networks: From Biology to Artificial Intelligence

Have you ever wondered how artificial intelligence mimics the human brain? To truly understand neural networks, we must first explore the biological systems that inspired them. This course bridges the gap between cognitive neuroscience and computer science, taking you on a conceptual journey from biological neurons to artificial intelligence. You will gain a deep, foundational understanding of how both biological and artificial systems process, store, and retrieve information. What you'll learn: Understand the structural organization of the human brain, cerebral cortex, and biological memory; Map biological neural pathways to artificial neural network architectures; Analyze the structure and basic mechanics of the classic perceptron; Explore core learning theories and how memory-based learning applies to machine models; Discover modern neural network concepts, including activation functions and basic training dynamics; Examine how biological attention principles inspired modern transformer architectures. We begin with foundational neurobiology, exploring how the brain processes information, before transitioning into artificial perceptrons, learning algorithms, and modern network concepts. This text-based program is designed for complete beginners with no prior background in programming or advanced neuroscience. Start your journey into the fascinating intersection of neuroscience and artificial intelligence today.