Duke University
Large Language Model Operations (LLMOps) Specialization
13,016 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

(135 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

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

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: Generative AI
Category: Risk Management Framework
Category: MLOps (Machine Learning Operations)
Category: Python Programming
Category: Application Programming Interface (API)
Category: GitHub
Category: Semantic Web

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

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: Rust (Programming Language)
Category: Command-Line Interface
Category: Amazon Web Services
Category: Cloud Computing
Category: Large Language Modeling
Category: Serverless Computing
Category: Application Deployment
Category: Development Environment
Category: Integration Testing
Category: Generative AI
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: Data Lakes
Category: Large Language Modeling
Category: Generative AI
Category: Apache Spark
Category: Exploratory Data Analysis
Category: Jupyter
Category: MLOps (Machine Learning Operations)
Category: Machine Learning
Category: Extract, Transform, Load
Category: Data Science
Category: Databricks
Category: Data Transformation
Category: Data Ethics
Category: Prompt Engineering

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: PyTorch (Machine Learning Library)
Category: Application Programming Interface (API)
Category: Artificial Neural Networks
Category: Browser Compatibility
Category: Tensorflow
Category: Rust (Programming Language)
Category: Generative AI
Category: Machine Learning
Category: Application Deployment

Earn a career certificate

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Instructors

Derek Wales
Duke University
5 Courses27,209 learners
Noah Gift
Duke University
40 Courses186,721 learners
Alfredo Deza
Duke University
29 Courses143,933 learners

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Duke University

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