This course provides a comprehensive exploration of the fundamentals and advanced techniques in Natural Language Processing (NLP) and Large Language Models (LLMs). Explore essential concepts such as word representation, text classification, and sequence modeling, while gaining a deeper understanding of the transformative impact of transformer architectures. Master practical strategies for optimizing models through pretraining, fine-tuning, and prompting, and develop the expertise to evaluate and apply modern LLMs effectively using industry-standard metrics and benchmarks.

CILO-1: Explain core concepts in Natural Language Processing (NLP) and Large Language Models (LLMs), including word representation, text classification, and sequence modelling. CILO-2: Apply advanced methodologies, such as transformer architectures, to solve tasks like machine translation, language modelling, and sentiment analysis effectively. CILO-3: Develop and implement strategies to improve NLP model performance through pretraining, fine-tuning, and effective prompting techniques. CILO-4: Critically analyse the performance and efficiency of NLP models and modern LLMs using industry-standard metrics and benchmarks. CILO-5: Implement LLMs in practical applications, such as conversational AI, text summarization, and content generation, while addressing ethical and societal implications.