Duke University

Operationalizing LLMs on Azure

This course is part of Large Language Model Operations (LLMOps) Specialization

Taught in English

Some content may not be translated

Noah Gift
Alfredo Deza
Derek Wales

Instructors: Noah Gift

2,419 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.1

(10 reviews)

Intermediate level

Recommended experience

10 hours (approximately)
Flexible schedule
Learn at your own pace

What you'll learn

  • 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)

Details to know

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Recently updated!

January 2024

Assessments

4 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.1

(10 reviews)

Intermediate level

Recommended experience

10 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Large Language Model Operations (LLMOps) Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
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There are 4 modules in this course

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.

What's included

21 videos8 readings1 quiz1 discussion prompt

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.

What's included

18 videos4 readings1 quiz

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.

What's included

19 videos3 readings1 quiz

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.

What's included

20 videos7 readings1 quiz

Instructors

Noah Gift
Duke University
40 Courses118,323 learners

Offered by

Duke University

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