Price Prediction and Analysis Using Regression Techniques

Understanding what drives market value is a critical skill in modern data analytics. This text-based course guides you through the foundational concepts of analyzing data and building predictive models specifically tailored for price estimation. You will learn to transform raw transactional data into clean, structured features and apply robust regression algorithms. By studying step-by-step written explanations and practical code snippets, you will gain the confidence to analyze real-world price trends and evaluate model accuracy. What you'll learn: - Understand foundational concepts of linear and multiple regression analysis - Prepare, clean, and transform real-world datasets for predictive modeling - Implement modern feature engineering techniques to improve model performance - Build and train regression models to forecast prices accurately - Evaluate model predictions using key metrics like Mean Absolute Error and R-squared - Apply best practices in model validation to prevent overfitting The course begins with core definitions and statistical foundations before walking you through data preprocessing, model selection, and practical evaluation techniques. You will progress from basic data loading to deploying predictive workflows through structured reading and conceptual exercises. This course is designed for aspiring data analysts, business intelligence beginners, and anyone interested in predictive modeling, with no prior machine learning experience required. Start learning the fundamentals of price prediction today.