"Unlock the Power of LLMs: A Hands-On Journey to Master Cutting-Edge AI!"

Dive into the world of Large Language Models (LLMs) in this comprehensive 2-day workshop. This workshop is designed to equip AI engineers, NLP professionals, and developers with the practical skills to build, fine-tune, and deploy state-of-the-art LLMs while adhering to industry best practices in LLMOps.

Learning Objectives

By the end of this workshop, participants will

1. Understand the core principles of LLMs, including architecture, training cycles, and evaluation metrics.
2. Gain hands-on experience in supervised fine-tuning and building scalable LLM pipelines.
3. Learn how to implement Retrieval-Augmented Generation (RAG) for real-world applications.
4. Develop expertise in deploying end-to-end LLM solutions using cloud-based tools like AWS and Azure.
5. Master LLMOps practices, including orchestrators, monitoring, and continuous improvement.

Duration: 2 days

Day 1:  Foundations and Practical Skills 

1. Session 1: Introduction to LLM Engineering: Overview of LLM technology and the AI landscape, Core principles of LLM design and implementation.
2. Session 2: Data Pipelines and Preprocessing: Building robust data pipelines for LLMs, Hands-on exercise: Preprocessing datasets for model training.
3. Session 3: Fine-Tuning LLMs: Techniques for supervised fine-tuning, Hands-on exercise: Fine-tuning an open-source LLM.
4. Session 4: LLM Evaluation and Metrics: Evaluating model performance and addressing bias, Hands-on exercise: Using evaluation frameworks.

Day 2:   Advanced Applications and Deployment 

1. Session 1: LLMOps Best Practices, Exploring orchestrators and monitoring tools for LLMs, Case studies: Real-world LLMOps implementations.
2. Session 2: Building RAG Applications: Introduction to Retrieval-Augmented Generation, Hands-on exercise: Implementing a RAG pipeline.
3. Session 3: Deployment Strategies: Deploying LLM solutions with AWS and other cloud tools, Hands-on exercise: Deploying a fine-tuned LLM.
4. Session 4: Final Project and Q&A: Participants implement a complete LLM solution using workshop concepts, Wrap-up and discussion of future trends in LLMs.