Unmanned Aerial Vehicles (UAVs), commonly known as drones, have seen a surge in popularity and adoption across various applications and industries. When integrated with sensor networks and Internet of Things (IoT) technologies, UAVs emerge as a powerful solution for data collection, monitoring, and remote sensing applications. This chapter provides an introduction to timely UAV-assisted IoT data collection, specifically leveraging Deep Reinforcement Learning (DRL). It begins by offering a brief introduction to the Age of Information (AoI) concept, defining it as the time elapsed between data generation and its arrival at the destination. Subsequently, a background on DRL is provided. The chapter then delves into UAV-assisted IoT networks, outlining their architectures, underlying assumptions, and diverse applications. A more in-depth discussion on AoI follows, covering key factors that impact timely data reception in UAV-IoT scenarios, including network size, battery status, flight distance, UAV speed and velocity, UAV altitude, and data size. Common assumptions for AoI-based UAV-IoT applications are also discussed. Finally, the chapter concludes by investigating important design considerations for AoI-aware UAV-assisted IoT networks and examining how DRL can effectively optimize system performance for AoI minimization.