Foundations of Data Analytics: Python, SQL, and Applied Statistics

Data is the backbone of modern business decision-making, but knowing how to extract, clean, and interpret it can feel overwhelming. This course provides a clear, structured path to mastering the essential technical skills required to start your journey in data analytics. You will transition from a complete beginner to a confident data explorer. By reading through guided explanations and analyzing real-world scenarios, you will learn how to write efficient database queries, program with Python to manipulate datasets, and apply statistical tests to validate business hypotheses. What you'll learn: - Understand fundamental data concepts, terminology, and the typical workflow of a data analyst. - Write SQL queries using advanced techniques like window functions, common table expressions (CTEs), and subqueries. - Process and analyze datasets using Python, leveraging modern libraries for data manipulation. - Calculate key product and business metrics to extract actionable insights from raw data. - Apply basic statistics and hypothesis testing to make data-driven decisions. - Practice writing clean, readable Python code using modern formatting and type hints. This course begins with foundational definitions of data structures and databases before moving into practical SQL querying. You will then transition to Python programming for data manipulation, culminating in applied statistics and metric calculation through written walkthroughs and exercises. This text-based course is designed specifically for beginners with no prior coding or analytical experience. Anyone looking to build a structured foundation in data analytics will find this guide accessible and practical. Start reading today and take your first step toward mastering the tools of modern data analysis.