15 062 Data Mining Spring 2003

In today's digital economy, organizations capture massive amounts of data every second, yet few know how to turn this raw information into actionable business intelligence. This text-based course bridges the gap between complex statistical theory and practical managerial decision-making. You will transition from understanding basic data concepts to confidently analyzing datasets for patterns and trends. By studying real-world business scenarios, you will learn how to identify opportunities, predict customer behavior, and mitigate risks like fraud using modern data mining techniques. What you'll learn: Understand foundational data mining terminology, data warehousing concepts, and the data lifecycle; Identify patterns and trends in business datasets using core statistical and machine learning algorithms; Apply classification and clustering techniques to solve real-world problems like fraud detection and customer segmentation; Explore modern data preparation workflows using contemporary dataframe libraries; Evaluate data mining models to ensure accuracy and ethical compliance in business decision-making. The course begins with essential definitions and data structures before guiding you through exploratory data analysis, predictive modeling, and practical business case studies. Through written explanations and conceptual walkthroughs, you will build a solid analytical foundation. Designed entirely for beginners, this course requires no prior background in programming or advanced statistics, making it ideal for aspiring analysts, managers, and business students. Start reading today to unlock the hidden value in your organization's data.