Data Science and AI Principles: A Conceptual Introduction

Artificial intelligence and data-driven decision-making are reshaping every industry, yet the technical jargon can feel overwhelming. This course demystifies the core concepts of data science and AI without requiring a background in complex mathematics or programming. You will develop a strong conceptual foundation in how data is collected, analyzed, and used to train intelligent systems. By learning the fundamental principles behind algorithms, predictions, and ethical data use, you will be able to confidently participate in data-driven discussions and make informed strategic decisions. What you'll learn: Understand the fundamental terminology of data science, machine learning, and artificial intelligence; Analyze how prediction models, causality, and data visualization drive business decisions; Explore the principles of data wrangling and how data is prepared for analysis; Evaluate critical issues in data privacy, security, and modern ethical AI practices; Learn the basic concepts behind generative AI, prompt engineering, and modern retrieval-augmented systems. The course begins with foundational definitions of data and algorithms, then transitions into practical concepts of analysis, prediction, and modern AI applications, concluding with ethical frameworks. This text-based program is designed entirely for beginners, managers, and non-technical professionals with no prior coding or advanced math experience. Start reading today to build your literacy in the technologies shaping the future.