Online Course – Duke University’s Certified Professional Internship in Large Language Model Operations (LLMOps)

Improve your skills in running large language models. Gain knowledge in managing, deploying, and optimizing these models on various platforms such as Azure, AWS, Databricks, on-premises infrastructure, and open source solutions through hands-on projects.

Suggested by: Coursera (What is Coursera?)

Professional Certificate

Beginners

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Critical thinking skills
  • Troubleshooting
  • Communication capabilities
  • Teamwork
  • Time management
  • Flexibility and ability to adapt to changes
  • Technological skills
  • Creative thinking
  • Organization and planning
  • Understanding complex issues

What you will learn in the course

Courses for which the course is suitable

  • Machine Learning Engineer
  • DevOps Engineer
  • Cloud Architect
  • AI Infrastructure Expert
  • LLMOps Consultant

Internship – Series of 6 courses

Master the world of large language models with this comprehensive specialization from Coursera and Duke University, a leading program in data science and artificial intelligence. Delve into topics ranging from generative AI techniques to managing large open-source language models across platforms such as Azure, AWS, Databricks, on-premises, and more.

With hands-on projects and best practices, you’ll gain hands-on experience designing, deploying, and scaling powerful language models tailored to different uses. Demonstrate your new skills in managing large language models by tackling real-world challenges and building your own portfolio as an LLMOps professional, preparing you for roles such as:

  • Machine Learning Engineer
  • DevOps Engineer
  • Cloud Architect
  • AI Infrastructure Expert
  • LLMOps Consultant

Hands-on Learning Project

Through over 20 hands-on coding projects, such as:

  • Deploying large language models in the Azure and AWS cloud
  • Services like Databricks
  • Leveraging Azure AI Service to Build Applications
  • Creating Strong Guidelines with LLM Frameworks
  • Running local models using APIs and cloud services
  • Building a chatbot based on personal data with vector databases

Learn authentic, portfolio-ready experience in deploying, managing, and optimizing large language models. These projects are built by experts at leading institutions to help professionals tackle real-world challenges in LLMOps across platforms and applications.

Details of the courses that make up the specialization

Introduction to Generative Artificial Intelligence

Course 1

  • 37 hours
  • 4.6 (63 ratings)

Course Details

What you’ll learn
  • Learn to use generative artificial intelligence for automation.
  • Develop software solutions based on generative artificial intelligence.
  • Create solutions with Prompt Engineering to improve the productivity of generative AI.
Skills you will acquire
  • Category: Artificial Intelligence (AI)
  • Category: Data Science
  • Category: Machine Learning
  • Category: Large Language Models
  • Category: Databricks

Bringing large language models to life in Azure

Course 2

  • 10 hours
  • 4.3 (23 ratings)

Course Details

What you’ll learn
  • Acquire skills in using Azure to deploy and manage Large Language Models (LLMs).
  • Develop advanced skills in creating queries using Semantic Kernel to improve interactions with LLMs in the Azure environment.
  • Gain hands-on experience implementing templates and deploying applications with Generative Augmented Generation (RAG).
Skills you will acquire
  • Category: Artificial Intelligence (AI)
  • Category: Python Programming
  • Category: Gaining Insights in AI/ML
  • Category: Azure Cloud Services

Advanced Data Engineering

Course 3

  • 23 hours

Course Details

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 to store data at scale.
Skills you will acquire
  • Category: Machine Learning
  • Category: Generative Artificial Intelligence
  • Category: llamafile
  • Category: Open Source
  • Category: LLMs

Generative AI and Large Language Models on AWS

Course 4

  • 45 hours

Course Details

What you’ll learn
  • Learn to use AWS to build solutions with generative artificial intelligence.
  • Learn the fundamentals of AWS cloud computing to become proficient in machine learning on AWS.
  • Develop machine learning solutions using AWS services like Amazon Bedrock.
Skills you will acquire
  • Category: Online databases
  • Category: Queue Management
  • Category: Data Import/Export
  • Category: Database Management Systems

Databricks for local LLMs

Course 5

  • 27 hours

Course Details

What you’ll learn
  • Use Databricks for data engineering and machine learning work.
  • Create and design machine learning pipelines.
  • Use Llamafile and large local language models like Mixtral.
Skills you will acquire
  • Category: Artificial Intelligence (AI)
  • Category: Python Programming
  • Category: Machine Learning
  • Category: Generative Artificial Intelligence
  • Category: LLMs

Open source LLMOps solutions

Course 6

  • 35 hours

Course Details

What you’ll learn
  • Run large local language models.
  • Resign (Fine-tune) LLMs.
  • Use open source generative artificial intelligence.
Skills you will acquire
  • Category: AWS
  • Category: Cloud Computing
  • Category: Large Language Models
  • Category: Generative Artificial Intelligence
  • Category: AWS Bedrock