This intensive hands-on course provides a practical introduction to training and fine-tuning Large Language Models for real-world data analysis tasks. Designed for technically minded professionals, it combines conceptual foundations with applied exercises using modern deep learning frameworks. Participants gain a clear understanding of how LLMs work, how they are trained, and how pertained models can be adapted to specific analytical problems. The course covers data preparation, fine-tuning techniques, and evaluation methods, with practical labs using TensorFlow and PyTorch to reinforce learning.
Beyond core workflows, the programme explores advanced topics such as transfer learning, domain adaptation, and multitask learning, alongside ethical considerations and bias management. By the end of the course, attendees are equipped to fine-tune LLMs effectively, interpret their outputs, and deploy them responsibly within data analysis pipelines.
Pre-requisites: A solid appreciation of AI and machine learning concepts is required.
