Data Science Fundamentals: Inference and Modeling

Understanding how to draw valid conclusions from data is the core skill of any successful data analyst or scientist. This text-based course guides you from foundational statistical concepts to building reliable predictive models. You will learn how to transition from simple data observation to making confident, data-driven predictions. What you'll learn: Understand foundational concepts of probability, estimation, and statistical significance; Apply hypothesis testing and confidence intervals to validate your data assumptions; Build and interpret linear and logistic regression models for prediction; Practice modern data techniques, including basic resampling methods and model validation; Explore how to identify and avoid common statistical bias in your analyses. This course begins with essential terminology and the mathematical foundations of inference, then moves step-by-step into practical modeling techniques with clear code examples. It is designed for beginners who want to build a strong, practical foundation in statistical data analysis without any prior modeling experience. Start reading today to unlock the power of statistical modeling.