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

Included with Coursera Plus

Get in-depth knowledge of a subject
4.4

(155 reviews)

Beginner level

Recommended experience

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

(155 reviews)

Beginner level

Recommended experience

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

What you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Taught in English
69 practice exercises

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  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
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  • 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

Generative AI, Prompt Engineering, Large Language Modeling, OpenAI, Responsible AI, Python Programming, ChatGPT, GitHub, Multimodal Prompts, LLM Application, Application Programming Interface (API), Machine Learning, and Natural Language Processing

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

Microsoft Azure, Large Language Modeling, LLM Application, Application Deployment, Prompt Engineering, OpenAI, Application Programming Interface (API), Responsible AI, Cloud Computing, MLOps (Machine Learning Operations), Python Programming, and Scalability
Advanced Data Engineering

Advanced Data Engineering

Course 323 hours

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

MySQL, Apache Airflow, Workflow Management, Scalability, Data Pipelines, Data Import/Export, Operational Databases, Middleware, Database Management Systems, Database Management, Dataflow, Data Architecture, Data Infrastructure, Data Warehousing, Real Time Data, Database Systems, Performance Analysis, Performance Tuning, and Data Transformation
GenAI and LLMs on AWS

GenAI and LLMs on AWS

Course 446 hours

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

Amazon Bedrock, AWS SageMaker, Cloud Computing, Large Language Modeling, MLOps (Machine Learning Operations), Continuous Monitoring, Data Ethics, Responsible AI, Generative AI, Application Deployment, Serverless Computing, Secure Coding, and Amazon Web Services
Databricks to Local LLMs

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

Data Pipelines, Large Language Modeling, Databricks, Data Transformation, Generative AI, Responsible AI, Data Lakes, CI/CD, Data Science, Machine Learning, MLOps (Machine Learning Operations), Apache Spark, Data Analysis, Extract, Transform, Load, and LLM Application
Open Source LLMOps Solutions

Open Source LLMOps Solutions

Course 636 hours

What you'll learn

  • Run local large language models

  • Fine-tune LLMs

  • Use open-source generative AI

Skills you'll gain

Open Source Technology, Large Language Modeling, Natural Language Processing, Machine Learning, Generative Model Architectures, Containerization, Application Deployment, Application Programming Interface (API), Prompt Engineering, and LLM Application

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Instructors

Derek Wales
Duke University
5 Courses30,139 learners
Noah Gift
Duke University
40 Courses196,557 learners
Alfredo Deza
Duke University
29 Courses153,174 learners

Offered by

Duke University

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