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Operationalizing LLMs on Azure
Noah Gift,
Alfredo Deza,
and
Derek Wales
Noah Gift,
Alfredo Deza,
and
Derek Wales
This course is designed for individuals at both an intermediate and beginner level, including data scientists, AI enthusiasts, and professionals seeking to harness the power of Azure for Large Language Models (LLMs). Tailored for those with foundational programming experience and familiarity with Azure basics, this comprehensive program takes you through a four-week journey. In the first week, you'll delve into Azure's AI services and the Azure portal, gaining insights into large language models, their functionalities, and strategies for risk mitigation. Subsequent weeks cover practical applications, including leveraging Azure Machine Learning, managing GPU quotas, deploying models, and utilizing the Azure OpenAI Service. As you progress, the course explores nuanced query crafting, Semantic Kernel implementation, and advanced strategies for optimizing interactions with LLMs within the Azure environment. The final week focuses on architectural patterns, deployment strategies, and hands-on application building using RAG, Azure services, and GitHub Actions workflows. Whether you're a data professional or AI enthusiast, this course equips you with the skills to deploy, optimize, and build robust large-scale applications leveraging Azure and Large Language Models.
Register for this course and see more details by visiting:
OpenCourser.com/course/ac3ebu/operationalizing
What's inside
Syllabus
Introduction to LLMOps with Azure
This week, 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.
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Syllabus
Introduction to LLMOps with Azure
This week, 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.
Read more
LLMs with Azure
This week, 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
This week, 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
This week, 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.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops foundational knowledge and skills for using Azure Large Language Models (LLMs) for industry applications
Teaches industry-standard techniques and best practices for deploying LLMs using Azure
Covers a wide range of topics in using LLMs with Azure, from basics to advanced techniques
Provides opportunities for hands-on practice through assignments and exercises
Emphasizes risk mitigation and responsible use of LLMs
Taught by experienced instructors who are recognized for their work in the field of LLMs
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Activities
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Operationalizing LLMs on Azure.
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Career center
Learners who complete Operationalizing LLMs on Azure will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. They then use this information to make recommendations and predictions. This course may be useful in providing a foundation for understanding the role of LLMs in data analysis and how to use them to collect, clean, and analyze data to identify trends and patterns.
Data Scientist
Data Scientist
Data Scientists use data to solve business problems. They collect, clean, and analyze data to identify trends and patterns. They then use this information to make recommendations and predictions. This course may be useful in providing a foundation for understanding the role of LLMs in data science and how to use them to solve business problems.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build and deploy machine learning models. They work with data scientists to understand the business problem and then design and implement machine learning solutions. This course may be useful in providing a foundation for understanding the role of LLMs in machine learning and how to use them to build and deploy machine learning models.
Product Manager
Product Manager
Product Managers manage the development and launch of new products. They work with engineers, designers, and marketers to bring new products to market. This course may be useful in providing a foundation for understanding the role of LLMs in product management and how to use them to develop and launch new products.
Systems Architect
Systems Architect
Systems Architects envision and create the overall architecture of a system, including data storage, security, and user experience. They may also manage teams of engineers and oversee the implementation and maintenance of the system. This course may be useful in providing a foundation for understanding the role of LLMs in complex systems and how to integrate them effectively.
Cloud Architect
Cloud Architect
Cloud Architects design, build, and manage cloud computing systems. They work with clients to understand their business needs and then design and implement cloud solutions that meet those needs. This course may be useful in providing a foundation for understanding the role of LLMs in cloud computing and how to integrate them effectively.
Software Engineer
Software Engineer
Software Engineers design, build, and maintain software systems. They work with users to understand their needs and then design and implement software solutions that meet those needs. This course may be useful in providing a foundation for understanding the role of LLMs in software development and how to use them to build and maintain software systems.
Information Architect
Information Architect
Information Architects design and organize information systems. They work with users to understand their needs and then design and implement systems that meet those needs. This course may be useful in providing a foundation for understanding the role of LLMs in information architecture and how to use them to design and organize information systems.
Trainer
Trainer
Trainers teach people how to use software and other technical products. They work with learners to understand their needs and then develop and deliver training materials that meet those needs. This course may be useful in providing a foundation for understanding the role of LLMs in training and how to use them to develop and deliver training materials.
Web Developer
Web Developer
Web Developers design and develop websites. They work with clients to understand their needs and then design and develop websites that meet those needs. This course may be useful in providing a foundation for understanding the role of LLMs in web development and how to use them to design and develop websites.
Technical Writer
Technical Writer
Technical Writers create documentation for software and other technical products. They work with engineers and other technical experts to understand the product and then write documentation that is clear and easy to understand. This course may be useful in providing a foundation for understanding the role of LLMs in technical writing and how to use them to create documentation for software and other technical products.
User Experience Designer
User Experience Designer
User Experience Designers design the user interface for software and other products. They work with users to understand their needs and then design interfaces that are easy to use and visually appealing. This course may be useful in providing a foundation for understanding the role of LLMs in user experience design and how to use them to design user interfaces that are easy to use and visually appealing.
Business Analyst
Business Analyst
Business Analysts analyze business processes and identify opportunities for improvement. They work with stakeholders to understand their needs and then design and implement solutions that meet those needs. This course may be useful in providing a foundation for understanding the role of LLMs in business analysis and how to use them to analyze business processes and identify opportunities for improvement.
Consultant
Consultant
Consultants provide advice to businesses on how to improve their operations. They work with clients to identify problems and then develop and implement solutions. This course may be useful in providing a foundation for understanding the role of LLMs in consulting and how to use them to provide advice to businesses on how to improve their operations.
Project Manager
Project Manager
Project Managers plan and execute projects. They work with stakeholders to define project goals and objectives and then develop and implement plans to achieve those goals. This course may be useful in providing a foundation for understanding the role of LLMs in project management and how to use them to plan and execute projects.
For more career information including salaries, visit:
OpenCourser.com/course/ac3ebu/operationalizing
Reading list
We've selected nine books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Operationalizing LLMs on Azure.
Provides a comprehensive overview of deep learning for NLP. It covers a wide range of topics, including word embeddings, recurrent neural networks, and transformers.
Save
Provides a comprehensive overview of deep learning. It covers a wide range of topics, including the different types of deep learning models, the challenges of developing deep learning systems, and the applications of deep learning.
Provides a comprehensive overview of statistical learning, which is the foundation of many machine learning algorithms. It valuable resource for anyone who wants to learn the theoretical underpinnings of machine learning.
Save
Provides a comprehensive overview of the history of AI. It covers a wide range of topics, including the different approaches to AI development, the challenges of developing AI systems, and the implications of AI for the future of work and society.
Provides a practical guide to machine learning with R. It covers a wide range of topics, including data preprocessing, feature engineering, and model evaluation.
Provides a practical guide to machine learning with Python. It covers a wide range of topics, including data preprocessing, feature engineering, and model evaluation.
Provides a comprehensive overview of NLP, with a focus on Python implementations. It valuable resource for anyone who wants to learn how to use Python for NLP tasks.
Provides a collection of recipes for common machine learning tasks in Python. It valuable resource for anyone who wants to learn how to use Python for machine learning tasks.
Provides a gentle introduction to machine learning. It valuable resource for anyone who wants to learn the basics of machine learning without getting bogged down in the details.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/ac3ebu/operationalizing
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Effort
5 weeks, 5 hours/week
Level
Intermediate
Via
Coursera
Institution
Duke University
Instructors
Noah Gift
Alfredo Deza
Derek Wales
Language
English
Transcripts
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This course belongs to a
collection
called
Large Language Model Operations (LLMOps). It's comprised of five courses:
- Databricks to Local LLMs
- Open Source LLMOps Solutions
- Operationalizing LLMs on Azure (viewing)
- GenAI and LLMs on AWS
- Advanced Data Engineering
Good to know
Develops foundational knowledge and skills for using Azure Large Language Models (LLMs) for industry applications
Teaches industry-standard techniques and best practices for deploying LLMs using Azure
Covers a wide range of topics in using LLMs with Azure, from basics to advanced techniques
Provides opportunities for hands-on practice through assignments and exercises
Emphasizes risk mitigation and responsible use of LLMs
Taught by experienced instructors who are recognized for their work in the field of LLMs
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