This paper examines the challenges and opportunities in teaching Natural Language Processing (NLP) at the undergraduate level, particularly in the era of Large Language Models (LLMs). It discusses the diverse backgrounds of students, including those from computer science and non-computer science disciplines, and the need to incorporate Indian languages into the curriculum. The study identifies key challenges, such as integrating classical NLP methods with contemporary deep learning techniques, and outlines practical issues in syllabus design. By focusing on the unique context of Indian universities, this paper offers actionable recommendations for educators to enhance NLP education. The insights and strategies proposed aim to address the evolving landscape of NLP and prepare students for the demands of the field.