Duke University
Large Language Model Operations (LLMOps) Specialization
12,960 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

(134 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

(134 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: Data Ethics
Category: Machine Learning
Category: Artificial Intelligence
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Natural Language Processing
Category: Open Source Technology
Category: Application Deployment
Category: Python Programming

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

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: Database Management Systems
Category: Big Data
Category: Databases
Category: NoSQL
Category: Data Warehousing
Category: Database Systems
Category: Data Import/Export
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: Serverless Computing
Category: Amazon Web Services
Category: Large Language Modeling
Category: Cloud Computing
Category: Rust (Programming Language)
Category: Command-Line Interface
Category: Debugging
Category: Generative AI
Category: Development Environment
Category: Application Deployment
Category: Integration Testing

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: Generative AI
Category: Data Lakes
Category: Apache Spark
Category: Data Ethics
Category: Databricks
Category: Extract, Transform, Load
Category: Data Transformation
Category: Machine Learning
Category: Data Science
Category: MLOps (Machine Learning Operations)
Category: Exploratory Data Analysis
Category: Jupyter
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: Cross Platform Development
Category: Natural Language Processing
Category: Large Language Modeling
Category: Application Programming Interface (API)
Category: Rust (Programming Language)
Category: Artificial Neural Networks
Category: Browser Compatibility
Category: Application Deployment
Category: Tensorflow
Category: PyTorch (Machine Learning Library)
Category: Generative AI
Category: Machine Learning

Earn a career certificate

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Instructors

Derek Wales
Duke University
5 Courses27,068 learners
Noah Gift
Duke University
40 Courses186,301 learners
Alfredo Deza
Duke University
29 Courses143,539 learners

Offered by

Duke University

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