Descriptive and Predictive Analytics for Data Science

Every organization sits on a goldmine of historical data, but the real value lies in understanding what happened and forecasting what comes next. This course bridges the gap between historical analysis and future prediction, giving you the essential toolkit to turn raw data into actionable insights. You will transition from simply reading data reports to actively modeling future outcomes, gaining a solid understanding of how descriptive statistics summarize the past and how predictive modeling techniques anticipate future trends. What you'll learn: Understand foundational statistical concepts, data distributions, and core terminology; Analyze historical datasets using descriptive analytics to identify key trends and patterns; Explore predictive modeling techniques, including regression and classification basics; Apply modern data tools and libraries like pandas to clean and prepare data for analysis; Evaluate model performance using key metrics to ensure reliable forecasts; Interpret data-driven insights to make informed, strategic decisions. The course starts with essential definitions and data concepts before guiding you through data exploration and practical modeling workflows. Through clear explanations and written exercises, you will build a strong foundation in modern data analysis. Designed entirely for beginners, this course requires no prior background in statistics or programming. Start your journey into data science and learn how to unlock the predictive power of your data today.