Intelligent Vehicular Networks (IVNs) are critical to the future of transportation, combining advanced networking technologies with vehicular systems to improve safety, traffic efficiency, and user experience. Deep learning plays a pivotal role in analyzing the vast data generated by these systems, enabling smarter decision-making, autonomous driving, and real-time communication between vehicles (V2V), vehicles and infrastructure (V2I), or vehicles and everything else (V2X).Intelligent Vehicular Networks using Deep Learning address critical challenges in transportation systems, from traffic management and safety to cybersecurity and energy efficiency. With the increasing push for smart cities and autonomous vehicles, these research directions offer innovative solutions and immense practical applications.