Overview of machine learning techniques, 5G/6G communication system architecture and AI convergence, O-RAN and data-driven network control, clustering techniques for UAV localization, time-series models such as LSTM for channel estimation and beam tracking, reinforcement learning and multi-agent decision-making in networks, supervised learning for traffic classification, unsupervised learning and explainable AI for anomaly detection, ML-based optimization in wireless networks, hands-on assignments using Jupyter notebooks, Sionna-based simulations for network/system-level modeling, and a final project on selected use cases in communication systems.

Any versions of the following books:
Applications of Machine Learning in Wireless Communications, by Ruisi He; Ruisi Zhiguo Ding
Machine Learning and Wireless Communications, by Yonina C. Eldar, Andrea Goldsmith, Deniz Gündüz, H. Vincent Poor
Wireless Communications, by Andreas F. Molisch