Artificial Intelligence and Neural Networks: A Non-Technical Introduction

Are you curious about Artificial Intelligence but overwhelmed by the technical jargon? This course provides a clear, accessible entry point into the world of AI and machine learning. By the end of this course, you will move past the hype and develop a foundational understanding of how modern AI systems, including neural networks, operate. You will gain the literacy needed to evaluate AI tools, understand their capabilities and limitations, and apply practical AI strategies in your work or daily life without needing to write a single line of code. What you'll learn: * Understand the core concepts of Artificial Intelligence, Machine Learning, and Deep Learning, defining key terminology. * Learn how neural networks process information, including the basic structure of layers, nodes, and training data. * Apply foundational principles of effective prompt engineering to maximize results from large language models (LLMs). * Analyze the ethical considerations and potential biases inherent in modern AI systems. * Identify common AI applications across different industries, such as computer vision and natural language processing. The course begins by establishing essential AI terminology and history, progresses through the mechanics of neural networks, and concludes with practical discussions on application and responsible usage. The material is presented entirely through written explanations and conceptual examples. This course is designed for absolute beginners—managers, students, or professionals from non-technical backgrounds—who want a fast, clear start in AI literacy. No prior technical knowledge, programming experience, or specific mathematical background is required. Start building your essential AI literacy today.