Duke University
Large Language Model Operations (LLMOps) Specialization
13,074 enrolled
Duke University

Large Language Model Operations (LLMOps) Specialization

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.

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Get in-depth knowledge of a subject

(136 reviews)

Beginner level

Recommended experience

Flexible schedule
5 months at 10 hours a week
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject

(136 reviews)

Beginner level

Recommended experience

Flexible schedule
5 months at 10 hours a week
Earn a career credential
Share your expertise with employers

What you'll learn

What’s included

Shareable certificate

Add to your LinkedIn profile

Taught in English
69 practice exercises

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from Duke University

Specialization - 6 course series

What you'll learn

  • Learn to utilize Generative AI for automation.

  • Develop Generative AI software solutions.

  • Build solutions with Prompt Engineering to enhance Generative AI output.

Skills you'll gain

Category: Generative AI
Category: Prompt Engineering
Category: Large Language Modeling
Category: OpenAI
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Open Source Technology
Category: Machine Learning
Category: Python Programming
Category: Natural Language Processing
Category: Data Ethics
Category: Application Deployment
Category: Artificial Intelligence

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)

Skills you'll gain

Category: Microsoft Azure
Category: Large Language Modeling
Category: Application Deployment
Category: Prompt Engineering
Category: OpenAI
Category: GitHub
Category: MLOps (Machine Learning Operations)
Category: Python Programming
Category: Semantic Web
Category: Application Programming Interface (API)
Category: Risk Management Framework
Category: Generative AI

What you'll learn

  • 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

Skills you'll gain

Category: MySQL
Category: Apache Airflow
Category: Data Pipelines
Category: Scalability
Category: Flask (Web Framework)
Category: Data Import/Export
Category: Database Management Systems
Category: Big Data
Category: Database Systems
Category: Databases
Category: NoSQL
Category: Data Warehousing
Category: Data Processing

What you'll learn

  • 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.

Skills you'll gain

Category: Prompt Engineering
Category: Amazon Web Services
Category: Large Language Modeling
Category: Cloud Computing
Category: Command-Line Interface
Category: Serverless Computing
Category: Rust (Programming Language)
Category: Development Environment
Category: Application Deployment
Category: Generative AI
Category: Integration Testing
Category: Debugging

What you'll learn

  • Use Databricks for data engineering and ML workloads

  • Create and design ML pipelines

  • Use Llamafile and other local LLMs like Mixtral

Skills you'll gain

Category: Data Pipelines
Category: Large Language Modeling
Category: Data Lakes
Category: Generative AI
Category: Machine Learning
Category: Apache Spark
Category: Data Ethics
Category: Data Transformation
Category: Databricks
Category: Jupyter
Category: Exploratory Data Analysis
Category: Data Science
Category: Prompt Engineering
Category: Extract, Transform, Load
Category: MLOps (Machine Learning Operations)

What you'll learn

  • Run local large language models

  • Fine-tune LLMs

  • Use open-source generative AI

Skills you'll gain

Category: Open Source Technology
Category: Natural Language Processing
Category: Cross Platform Development
Category: Large Language Modeling
Category: Application Programming Interface (API)
Category: PyTorch (Machine Learning Library)
Category: Generative AI
Category: Application Deployment
Category: Artificial Neural Networks
Category: Browser Compatibility
Category: Rust (Programming Language)
Category: Tensorflow
Category: Machine Learning

Earn a career certificate

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Instructors

Derek Wales
Duke University
5 Courses27,365 learners
Noah Gift
Duke University
40 Courses187,241 learners
Alfredo Deza
Duke University
29 Courses144,436 learners

Offered by

Duke University

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