Generative AI is a technology that uses data to produce something new in response to a prompt entered by a human. Large Language Models (LLM) is a type of generative AI, the latest language model that can understand and interpret natural language. LLMs are very large deep-learning models which are pre-trained on huge amounts of existing data. LLMs can be used for text generation, code generation, translation, summarization, conversational AI and chatbots. With the advent of the latest technologies, one of the challenges faced in LLM is that the model pre-trained may become obsolete in future. The Retrieval Augmented Generation (RAG) technique is helpful in such cases as it augments the existing data as an external source and can be integrated with the pre-trained LLM. The paper uses Generative AI using LLM and RAG for the development of smart e-learning course content in the field of learning science to assist subject matter experts (SME) or instruction designers. The tool simplifies presenting complex information without compromising accuracy. The SME finds it easy to balance content creation with their other professional responsibilities. The scope of the paper is to generate content consisting of course objectives, course outcomes, and questionnaires for assessment. The course content thus generated in a certain required format is assessed by the subject matter expert to fine-tune.