Artificial Intelligence (AI) is rapidly reshaping how we live, work, and interact with the world. This beginner-friendly course offers a comprehensive introduction to key AI concepts, designed for anyone curious about intelligent technologies and their real-world impact.You'll learn the fundamentals of machine learning, neural networks, natural language processing (NLP), computer vision, and the difference between narrow AI and artificial general intelligence (AGI). The course explains how parameters influence model outputs, how AI systems are trained, and how large language models (LLMs) work within practical workflows—covering everything from data input to training cycles and feedback.Each lecture includes a short reinforcement quiz to help solidify your understanding and encourage retention. With clear, jargon-free explanations, learners gain a strong foundation in AI model architecture, types of learning (like supervised, unsupervised, and reinforcement learning), and ethical implications of modern AI systems.Authored by an experienced software developer with 35+ years in the tech industry and a passion for science and innovation, this course prioritizes clarity, curiosity, and real-world relevance. Whether you're a student, professional, or tech enthusiast, you'll finish with the confidence to engage in AI discussions and explore advanced topics. No prior experience required—just basic English comprehension and an internet-enabled device.
What you'll learn
understand key AI concepts
grasp the fundamentals of machine learning
recognize the ethical implications of AI
differentiate between narrow AI and AGI
explore natural language processing and computer vision
Course objectives
introduce essential AI concepts
demonstrate practical workflows of AI systems
explore types of learning including supervised and unsupervised