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September 26, 2024
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Master Large Language Model Operations. Develop expertise in deploying, managing, and optimizing large language models across various platforms including Azure, AWS, Databricks, local infrastructure, and open source solutions through hands-on projects.
Instructors: Derek Wales
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(112 reviews)
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Beginner level
Beginner programming experience in any language. Familiarity with Linux, command line interfaces, or cloud services helpful but not required.
(112 reviews)
Recommended experience
Beginner level
Beginner programming experience in any language. Familiarity with Linux, command line interfaces, or cloud services helpful but not required.
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Master the world of Large Language Models through this comprehensive specialization from Coursera and Duke University, a top Data Science and AI program. Dive into topics ranging from generative AI techniques to open source LLM management across various platforms such as Azure, AWS, Databricks, local infrastructure, and beyond. Through immersive projects and best practices, gain hands-on experience in designing, deploying, and scaling powerful language models tailored for diverse applications. Showcase your newly acquired LLM management skills by tackling real-world challenges and building your own portfolio as a proficient LLMOps professional preparing you for roles such as Machine Learning Engineer, DevOps Engineer, Cloud Architect, AI Infrastructure Specialist, or LLMOps Consultant.
Applied Learning Project
Through over 20 hands-on coding projects like deploying large language models on Azure and AWS clouds or services such as Databricks, utilizing the Azure AI Service for building applications, creating powerful prompts with LLM frameworks, running local LLM models using external APIs and cloud services, and constructing a chatbot based on personal data with vector databases, learners will acquire authentic, portfolio-ready experience in deploying, managing, and optimizing large language models. These projects are designed by experts at leading institutions to help professionals tackle real-world LLMOps challenges across various platforms and applications.
Learn to utilize Generative AI for automation.
Develop Generative AI software solutions.
Build solutions with Prompt Engineering to enhance Generative AI output.
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)
Create and manage data pipelines and their lifecycle
Connect and work with message queues to manage data processing
Use vector, graph, and key/value databases for data storage at scale
Learn to use AWS to build solutions with Generative AI.
Learn the basics of AWS cloud computing to enable you to be proficient with machine learning on AWS.
Develop machine learning solutions using AWS services like Amazon Bedrock.
Use Databricks for data engineering and ML workloads
Create and design ML pipelines
Use Llamafile and other local LLMs like Mixtral
Run local large language models
Fine-tune LLMs
Use open-source generative AI
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
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This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.
This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.
Financial aid available,