LLMOps: what it is and why you should care
LLMOps, short for Large Language Model Operations, is all about answering one question: “How can I actually build something with LLMs?” It focuses on the practical challenges of using LLMs in production, integrating LLMs into existing systems, and getting an LLM to perform both reliably and safely.
Have you ever thought about building an application with large language models (LLMs)? Maybe there’s a personal chatbot you’d like to build, or maybe you’d like to improve your sales process with an LLM? Well, if you want to actually build with LLMs—not just make a flashy demo—you’re going to need more than just a script that runs locally on your computer. You’re going to need infrastructure and tools to help you train, deploy, prompt, and manage your LLMs.
Unfortunately, many of the popular LLM courses today focus exclusively on theory or building a simple proof-of-concept in a Jupyter Notebook, paying little attention to practical operations.
To help address this knowledge gap, Udacity has partnered with Comet ML, the machine learning platform used by companies like Uber, Google, and Zappos, to bring you this free, short course, LLMOps: Building Real-World Applications With Large Language Models.
Whether you’re a relative newcomer to ML or a seasoned data scientist who has built 1,000s of models, this self-paced course will teach you everything you need to know to build real-world applications with large language models.
Course Content
In our LLMOps course, you will explore the frontiers of LLM research, become proficient in some of the most popular LLM tools in the industry, and develop a comprehensive understanding of the LLMOps lifecycle. Specific skills you’ll build include:
- How to finetune, evaluate, and deploy LLMs
- How to use prompt engineering to control your LLM’s output
- How to monitor and debug your LLM for performance and safety
- How to build actual products around an LLM
This course is largely project-based, which means that you’ll be building real, functional applications with your own data as you progress.
Lesson 1: Introduction to LLMs
We’ll dive into the fundamentals of large language models, looking at the unique infrastructure and engineering challenges posed by LLMs. By the end of the lesson, you’ll have a complete understanding of what goes into engineering an LLM-powered product.
Lesson 2: Working with LLMs
You’ll begin working hands-on with LLMs in this lesson. After learning how to select an LLM for your particular task, you’ll take a deep dive into the world of prompt engineering, learning the most advanced techniques for prompting your LLM. Finally, you’ll learn how to finetune, evaluate, and optimize your LLM with tools like Comet LLM.
Lesson 3: LLMOps in Practice
In this lesson, you’ll go from working with LLMs to working with LLMs in production. You’ll take a crash course on model versioning, experiment tracking, and model management. You’ll then explore Comet LLM, a framework for debugging and analyzing your LLM. Finally, you’ll learn how to deploy your LLM efficiently and scalably with production monitoring.
Lesson 4: Case Studies & Applications of LLMs
You’ll begin building real world applications with LLMs in this lesson. First, you’ll explore a survey of some of existing LLM-powered products. Then, you’ll get the chance to build three different projects, including a reliable customer support bot, an LLM-powered evaluation system, and a clickbait detector.
Lesson 5: Advanced Topics in LLMs and LLMOps
Now that you’re proficient in building with LLMs, we’ll dive into some more advanced subjects. You’ll first learn about the challenges of using an LLM at scale, before diving into topics around LLM safety and fairness. You’ll learn about securing your LLM from bad actors, as well as testing and monitoring your LLMs for privacy, fairness, and bias risks.
Lesson 6: The Future of LLMOps
To finish the course, you will explore the future of the field. We’ll look at some of the most exciting trends and challenges in the field of LLMs, take a zoomed-out view to see where LLMOps sits within the broader MLOps ecosystem, and build our own roadmap for the immediate future of LLMOps.
Your Instructor
The free Comet LLMOps course is taught by a world-class expert in Elvis Savaria. Elvis is the co-founder of DAIR.AI, where he leads all AI research, education, and engineering efforts. He focuses on training and building large language models and information retrieval systems. Previous to this, he was at Meta AI, where he supported and advised world-class products and teams such as FAIR, PyTorch, and Papers with Code. He was also previously an education architect at Elastic, where he developed the technical curriculum and courses for the Elastic Stack.
Enroll Today To Start Building
LLMs represent one of the most important technological developments of the last century. Every day more and more products are built on top of LLMs, solving real-world problems that were previously intractable. If you want to take part in this, then this course is for you. Enroll today, and in a matter of weeks, you’ll have everything you need to build an LLM-powered application.
