Duke University
Large Language Model Operations (LLMOps) Specialization

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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.

Derek Wales
Noah Gift
Alfredo Deza

Instructors: Derek Wales

13,518 already enrolled

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Get in-depth knowledge of a subject
4.4

(145 reviews)

Beginner level

Recommended experience

5 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
4.4

(145 reviews)

Beginner level

Recommended experience

5 months at 10 hours a week
Flexible schedule
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: Application Programming Interface (API)
Category: OpenAI
Category: Machine Learning
Category: Natural Language Processing
Category: Artificial Intelligence
Category: GitHub
Category: Data Ethics
Category: Python Programming
Category: ChatGPT

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: Scalability
Category: OpenAI
Category: Application Deployment
Category: Prompt Engineering
Category: Software Architecture
Category: GitHub
Category: Artificial Intelligence
Category: Risk Management Framework
Category: Application Programming Interface (API)
Category: Python Programming
Category: MLOps (Machine Learning Operations)
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: Apache Airflow
Category: MySQL
Category: Data Pipelines
Category: Workflow Management
Category: Database Management Systems
Category: Scalability
Category: Performance Analysis
Category: Database Management
Category: Database Systems
Category: Dataflow
Category: Middleware
Category: Data Transformation
Category: Data Architecture
Category: Data Warehousing
Category: Data Import/Export
Category: Data Infrastructure
Category: Performance Tuning
Category: Real Time Data
Category: Operational Databases

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: Large Language Modeling
Category: Cloud Computing
Category: Rust (Programming Language)
Category: AWS SageMaker
Category: Personally Identifiable Information
Category: Amazon CloudWatch
Category: Generative AI
Category: Development Environment
Category: General Data Protection Regulation (GDPR)
Category: Secure Coding
Category: Data Ethics
Category: MLOps (Machine Learning Operations)
Category: Software Development Tools
Category: Amazon Elastic Compute Cloud
Category: Amazon Web Services
Category: Continuous Monitoring

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: Databricks
Category: Open Source Technology
Category: Generative AI
Category: Large Language Modeling
Category: Data Transformation
Category: Data Lakes
Category: CI/CD
Category: Data Processing
Category: Data Ethics
Category: Machine Learning
Category: Data Science
Category: Data Analysis
Category: Extract, Transform, Load
Category: Apache Spark
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: Large Language Modeling
Category: Tensorflow
Category: Application Deployment
Category: Machine Learning
Category: Containerization
Category: Generative AI
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Command-Line Interface
Category: Application Programming Interface (API)
Category: PyTorch (Machine Learning Library)

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Instructors

Derek Wales
Duke University
5 Courses28,416 learners
Noah Gift
Duke University
40 Courses190,495 learners
Alfredo Deza
Duke University
29 Courses147,508 learners

Offered by

Duke University

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