This lecture overviews the impact of the Large Language Models, particularly of ChatGPT language model in Education, e.g., in Universities. First it present the ChatGPT transformer structure and ChatGPT training. It also overviews ChatGPT capabilities in language processing (e.g., text translation, summarization, text sentiment analysis, dialogue tasks, misinformation detection, code understanding and generation). The ChatGPT implications on education are presented, notably its capabilities to reply exam questions, including mathematical and programming ones.  ChatGPT raises serious issues with respect to both its constructive use in education environments and its malicious use in course projects and exams. The impact of Large Language Models, and more generally Generative AI, in the structure of University education is detailed, as all sciences are increasingly mathematized and new scientific disciplines emerge (e.g., AI Science and Engineering) or are expected to emerge (e.g., Mind and Social Science and Engineering).  LLM memory/inference capabilities, limitations (e.g., halucinations), and open questions and regulatory proposals are presented. Finally, a possible overhaul of the education system at all levels is proposed to address social challenges coming out of the extensive LLM and Generative AI use.