This course introduces stochastic processes, focusing on their application in Electrical Engineering, Computer Science, and other related Engineering fields. Stochastic processes are vital for modeling systems affected by uncertainty, which is crucial in areas such as communications, signal processing, control systems. Students will explore mathematical foundations, including probability models, random variables, and statistical inference. Topics such as random vectors, Gaussian processes, and continuous-time random processes will be covered, providing essential tools for analyzing complex data. A key emphasis will be on applications in radar systems, demonstrating how stochastic models improve signal processing and system design. Additionally, students will learn how these concepts apply to IoT, where managing uncertainty in large data sets is critical for enhancing performance and reliability. By bridging multiple engineering disciplines, this course prepares students to tackle real-world challenges, equipping them with skills necessary for innovative solutions in an increasingly data-driven landscape.