Operationalizing LLMs on Azure

Duke University via Coursera

Go to Course: https://www.coursera.org/learn/llmops-azure

Introduction

Gain proficiency in leveraging Azure for deploying and managing Large Language Models (LLMs).

Develop advanced query crafting skills using Semantic Kernel to optimize interactions with LLMs within the Azure environment.

Acquire hands-on experience in implementing patterns and deploying applications with Retrieval Augmented Generation (RAG)

Syllabus

Introduction to LLMOps with Azure

In this module, you will learn how to get started with Azure and its AI services through an introduction to the Azure portal, and key offerings like Azure Machine Learning. You will also gain an understanding of large language models, including how they work, their benefits and risks, and strategies for mitigating those risks. Finally, you will be introduced to options for discovering, evaluating, and deploying pre-trained LLMs in Azure, including leveraging prompt engineering for responsible data grounding.

LLMs with Azure

In this module, you will learn to leverage Azure for Large Language Models (LLMs) by using Azure Machine Learning through its compute resources and managing GPU quotas and model deployments as well as Azure OpenAI Service. You will apply this knowledge by deploying a model and using its inference API using the Python programming language.

Extending with Functions and Plugins

In this module, you will discover the art of crafting nuanced queries for Large Language Models (LLMs) in Azure through the implementation of Semantic Kernel. You will gain insights into refining prompts, understand the dynamics of using system prompts, and explore advanced strategies to optimize your interaction with LLMs. You will apply these techniques hands-on to enhance your proficiency in leveraging Semantic Kernel within the Azure environment.

Building an End-to-End LLM application in Azure

In this module, you will explore architectural patterns and deployment of large language model applications. By studying RAG, Azure services, and GitHub Actions, you will learn how to build robust applications. You will apply your learning by implementing RAG with Azure search, creating GitHub Actions workflows, and deploying an end-to-end application.