Intelligent wireless networks using deep learning aim to address critical challenges in modern wireless communications. By leveraging advanced machine learning techniques, this research will contribute to the development of intelligent systems capable of self-optimizing, detecting anomalies, and enhancing overall network performance. The emphasis on practical applications alongside theoretical advancements will prepare researchers to make significant contributions to the future of wireless networking.Traditional wireless network management techniques often struggle to keep pace with the complexity and dynamic nature of modern networks. Deep learning offers powerful tools for analyzing vast amounts of data generated by wireless networks, enabling the development of intelligent systems capable of self-optimization, anomaly detection, and resource allocation. This series of PhD projects aims to explore innovative applications of deep learning in intelligent wireless networks to address these challenges.