This course provides a deep dive into supervised learning, demystifying the critical distinction between regression and classification models. You will first build a foundation by comparing how these algorithms learn from labeled data to make different types of predictions. The theory is then immediately applied to a telecom context, using regression to forecast signal strength and network traffic patterns. Concurrently, you will implement classification algorithms to automatically identify and categorize network anomalies and failures. Through hands-on projects, you will learn to select, train, and evaluate the right model for each specific engineering challenge. By the end, you will be equipped to design intelligent systems that enhance network reliability and performance.