Foundations of Probability for Data and Decision Making

In a world driven by data, understanding the laws of chance is essential for making sense of complex information and unpredictable events. This text-based course guides you through the core principles of probability, moving from basic definitions to the tools used in modern data science and risk analysis. What you'll learn: - Understand foundational concepts like sample spaces, events, and independence - Apply counting principles and combinatorics to solve probability problems - Master discrete and continuous random variables and their distributions - Calculate conditional probabilities and apply Bayes' Theorem to update beliefs - Practice interpreting the Law of Large Numbers and the Central Limit Theorem - Explore how probability models inform modern machine learning algorithms Starting with basic terminology and definitions, the course builds your intuition through clear written explanations and logic-based exercises that connect mathematical theory to practical data scenarios. It is designed specifically for beginners with no prior background in statistics, providing a structured path to mathematical literacy. Start building your foundation in the science of uncertainty today.