Data Science and Applied AI Fundamentals

Entering data science and artificial intelligence can feel overwhelming without a structured and accessible learning path. This course provides a clear foundation in statistical principles, data exploration, predictive modeling, and modern AI workflows. What you will learn: Understand foundational data science terminology, core mathematical concepts, and the standard analysis lifecycle. Clean, transform, and analyze tabular datasets using modern analytical patterns. Build baseline predictive models for regression and classification tasks. Apply modern artificial intelligence concepts, including foundation model basics and prompt design patterns. Evaluate model performance and diagnose common modeling issues like overfitting. The material begins with essential vocabulary and foundational data concepts before moving methodically into hands-on data manipulation, predictive analytics, and practical AI applications with explanatory code snippets. This course is designed specifically for complete beginners with no prior programming or advanced mathematics experience required. Begin reading today to develop practical, future-ready data skills at your own pace.