The PYTHON511-PYTHON514 Generative AI and Large Language Models (LLMs) training series introduces practical ways to work with Generative AI and large language models in research and applied settings. Rather than focusing on theory alone, the sessions are designed to help you understand how these tools work, what they can and cannot do, and where they can be applied effectively.
This PYTHON513 course builds on the foundations established in PYTHON512, shifting the focus from classification-based NLP workflows to generative AI and large language model (LLM) applications. You will explore how pre-trained LLMs are used to generate, transform, and manipulate text in more advanced and realistic scenarios. You will work hands-on with pre-trained generative language models to produce synthetic text, perform text transformation tasks such as translation, and apply LLMs in multi-language contexts. You will also learn how to control model behaviour through generation parameters, allowing you to balance factors such as coherence, diversity, and output length in practical applications.
Rather than focusing on model architecture or training large models from scratch, this course emphasises effective use of existing generative models. You will develop an understanding of the strengths and limitations of generative LLMs, explore common challenges such as hallucination and evaluation, and gain practical experience assessing model outputs in applied settings.
By the end of this course, you will be confident in using pre-trained generative language models for text generation, transformation, and multilingual NLP tasks, and be well prepared to apply these techniques in more advanced LLM systems and applications.