Duke University
Large Language Model Operations (LLMOps) Specialization
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

11,361 already enrolled

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Get in-depth knowledge of a subject
4.4

(120 reviews)

Beginner level

Recommended experience

5 months
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.4

(120 reviews)

Beginner level

Recommended experience

5 months
at 10 hours a week
Flexible schedule
Learn at your own pace

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Specialization - 6 course series

Introduction to Generative AI

Course 137 hours4.5 (122 ratings)

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: Data Analysis
Category: Data Ethics
Category: Generative AI
Category: Data Pipelines
Category: CI/CD
Category: Databricks
Category: Machine Learning
Category: Large Language Modeling
Category: Extract, Transform, Load
Category: Analytics
Category: Data Lakes
Category: MLOps (Machine Learning Operations)
Category: Data Science
Category: Apache Spark
Category: Data Governance
Category: Data Transformation

Operationalizing LLMs on Azure

Course 210 hours4.3 (35 ratings)

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

Advanced Data Engineering

Course 323 hours4.3 (11 ratings)

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: Containerization
Category: Command-Line Interface
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: PyTorch (Machine Learning Library)
Category: Tensorflow
Category: Generative AI
Category: Natural Language Processing
Category: Open Source Technology
Category: Application Programming Interface (API)
Category: Machine Learning
Category: Large Language Modeling
Category: Application Deployment

GenAI and LLMs on AWS

Course 446 hours4.7 (20 ratings)

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: Performance Tuning
Category: Data Pipelines
Category: Real Time Data
Category: Operational Databases
Category: Data Warehousing
Category: Data Architecture
Category: Database Management Systems
Category: Data Infrastructure
Category: Scalability
Category: Database Management
Category: Dataflow
Category: Workflow Management
Category: MySQL
Category: Data Transformation
Category: Performance Analysis
Category: Apache Airflow
Category: Database Systems
Category: Middleware

Databricks to Local LLMs

Course 527 hours

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: Prompt Engineering
Category: OpenAI
Category: GitHub
Category: Data Ethics
Category: Natural Language Processing
Category: Generative AI
Category: Application Programming Interface (API)
Category: Machine Learning
Category: ChatGPT
Category: Large Language Modeling
Category: Artificial Intelligence
Category: Python Programming

Open Source LLMOps Solutions

Course 636 hours4.7 (10 ratings)

What you'll learn

  • Run local large language models

  • Fine-tune LLMs

  • Use open-source generative AI

Skills you'll gain

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

Instructors

Derek Wales
Duke University
5 Courses23,533 learners
Noah Gift
Duke University
40 Courses174,653 learners
Alfredo Deza
Duke University
29 Courses132,134 learners

Offered by

Duke University

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