LLM Mastery: From Foundations to Deployment

Category: RiseAhead Programme - DataAhead

Module: LLM Mastery: From Foundations to Deployment

Module Description: The course is designed to provide participants with a comprehensive, hands-on understanding of Large Language Models (LLMs) and their applications in Generative AI (GenAI). It covers foundational concepts and practical tools, such as Python programming, Hugging Face libraries, and LLM architecture. Participants will gain the skills to build, fine-tune, and deploy LLMs for a wide range of applications, including text generation, retrieval-augmented generation (RAG), and customising outputs. The course emphasises real-world use cases, equipping learners to implement and optimise LLMs in various domains, from data collection and preprocessing to production deployment.

Objectives:

• By the end of the course, participants will gain:
• 1. Gain proficiency in Python for web crawling, dynamic content extraction, and data storage using BS4, Selenium, and the Hugging Face dataset store.
• 2. Master the use of Hugging Face libraries for NLP, image, and audio tasks through pipelines.
• 3. Develop expertise in Retrieval-Augmented Generation (RAG) systems, including vector databases and embedding optimization.
• 4. Acquire skills to fine-tune, evaluate, and deploy custom LLMs for specific use cases.
• 5. Learn advanced techniques such as prompt engineering, embedding strategies, and AI agent development.
• 6. Gain practical experience in optimising LLM performance and deploying models in production environments.
• 7. Understand the end-to-end LLM development cycle, from data collection to real-world deployment.

Method of Delivery: