Foundations of Artificial Intelligence: From Machine Learning to AI Ethics

Artificial intelligence is transforming every industry, yet understanding how these technologies actually work can feel overwhelming. This text-based course demystifies the core concepts of AI, breaking down complex algorithms into clear, readable explanations. You will transition from a curious observer to a knowledgeable professional capable of discussing machine learning, neural networks, and modern generative models with confidence. By the end of this course, you will understand how algorithms learn from data and how to evaluate the ethical implications of AI deployment. What you'll learn: - Understand the foundational definitions and differences between artificial intelligence, machine learning, and deep learning. - Explore how neural networks process information and how deep learning models are trained. - Analyze the mechanics behind computer vision and natural language processing, including modern large language models. - Apply basic prompt engineering principles to interact effectively with generative AI tools. - Evaluate ethical considerations, bias mitigation, and safety protocols in modern AI systems. The course begins with core terminology and historical context before guiding you through the practical mechanics of machine learning, neural networks, and domain-specific applications like computer vision. You will wrap up by exploring the critical landscape of AI safety and ethics through structured, text-based scenarios and conceptual exercises. This course is designed specifically for beginners with no prior programming or advanced mathematics background. Start reading today to build a future-proof understanding of artificial intelligence.