Free

LLMOps: Building Real-World Applications With Large Language Models

Course

The goal of this course is to teach you everything you need to build real-world, production software with large language models. Unlike other LLM-focused courses, our emphasis will not be on theory or on building simple proof-of-concept projects in Jupyter notebooks. We will instead be exploring the operations behind production-grade LLM applications. This includes, but is not limited to experiment management and model versioning, fine-tuning and prompt engineering, deployment, monitoring, and maintenance of LLMs, and AI safety and security (including how to protect against adversarial actors). Along the way, we'll build several full applications, including a chatbot, an evaluation system, and a clickbait detector. Finally, we'll look at the future of LLM and LLMOps.

Built in collaboration with

Comet

Intermediate

2 weeks

Completion Certificate

Last Updated January 30, 2024

Skills you'll learn:

Large Language Models • Comet ML • MLOps

Prerequisites:

Basic machine learning • Intermediate Python

Course Lessons

Lesson 1

Introduction to LLMOps

In this lesson, we will introduce LLMs and LLMOps, discuss the importance of LLMOps for real-world applications, overview the LLMOps lifecycle, and explain the difference between LLMOps and MLOps.

Lesson 2

Working with LLMs

In this lesson, we will strategize around model training and selection, fine-tune and improve LLMs with experiment tracking, revise evaluation approaches for LLMs, and explore prompt engineering.

Lesson 3

LLMOps in Practice

In this lesson, we will learn about model versioning and experiment management, explore different strategies for debugging LLMs, and deploy, monitor, and maintain LLMs in production.

Lesson 4

Case Studies & Applications of LLMOps

In this lesson, we will explore several real world applications of LLMs, build a reliable customer support chatbot, build an LLM-based evaluation system, and implement a clickbait detector.

Lesson 5

Advanced Topics in LLMs & LLMOps

In this lesson, we will explore challenges and strategies pertaining to running LLMs at scale, dive into safety and privacy concerns in AI, and learn about adversarial prompting and AI security.

Lesson 6

The Future of LLMOps

In this lesson, we will take a high-level view of LLMOps trends, look towards the future of LLMs and LLMOps, and explore the broader MLOps landscape.

Taught By The Best

Comet

Comet's mission is to empower practitioners and teams to achieve business value with AI. Comet builds tools that help data scientists, engineers, and team leaders accelerate and optimize machine learning and deep learning models. Organizations of every size—from academic teams to startups to enterprise companies—use Comet's platform to build better ML models faster.

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Demonstrate proficiency with practical projects

Projects are based on real-world scenarios and challenges, allowing you to apply the skills you learn to practical situations, while giving you real hands-on experience.

Gain proven experience
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Top-tier services to ensure learner success

Reviewers provide timely and constructive feedback on your project submissions, highlighting areas of improvement and offering practical tips to enhance your work.