LLMOps Course: Building with LLMs

FREE COURSE

LLMOps: Building Real-World Applications With Large Language Models

Course Launch: October 25th

Learn to build modern software with LLMs using the newest tools and techniques in the field.

Expert Instructors

Taught by industry leaders

Self-Paced

Learn at your own speed

Built with OpenAI

Use the latest models and APIs

Course Description

Level: Intermediate

Duration: 2 Weeks

Audience: Data Scientists/Software Engineers

Prerequisites: Basic ML knowledge, Python experience

Who is This For?

Data Scientists

Engineers

Students

Anyone curious about LLMs

Why This Course?

This is the only course completely focused on actually building real-world applications with large language models. We will cover some theory, but this is first and foremost in applied AI, not mathematics.

Taught By An Expert

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 (LLMs) 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 technical curriculum and courses for the Elastic Stack. A

What You'll Learn

Module 1. Introduction to LLMs

Brief introduction to LLMs

Explore the importance of LLMOps in LLM engineering

Breakdown the LLMOps lifecycle

Overview the difference between LLMOps and MLOps

Module 2. Working with LLMs

Discuss challenges and strategies in training LLMs

Learn how to select the best LLM for your task

Dive into prompt engineering and evaluation

Explore fine-tuning, optimization, and experiment tracking

Module 3. LLMOps in Practice

Introduce model versioning and management

Explore a reliable framework for debugging LLMs

Learn how to deploy LLMs efficiently

Setup production monitoring for LLMs

Module 4. Case Studies & Applications of LLMs

Explore real world applications of LLMs

Build a reliable customer support chatbot

Deploy an LLM-powered evaluation system

Construct a clickbait detector from scratch

Module 5. Advanced Topics in LLMs and LLMOps

Overview the most exciting trends in LLMOps

Discuss the role of LLMOps in the MLOps ecosystem

Build a roadmap for the immediate future of LLMs

Module 6. The Future of LLMOps

Understand the challenges of deploying LLMs at scale

Explore privacy and security concerns in LLMs

Learn to test for fairness, bias, and transparency

Brief introduction to LLMs

Explore the importance of LLMOps in LLM engineering

Breakdown the LLMOps lifecycle

Overview the difference between LLMOps and MLOps

Discuss challenges and strategies in training LLMs

Learn how to select the best LLM for your task

Dive into prompt engineering and evaluation

Explore fine-tuning, optimization, and experiment tracking

Introduce model versioning and management

Explore a reliable framework for debugging LLMs

Learn how to deploy LLMs efficiently

Setup production monitoring for LLMs

Explore real world applications of LLMs

Build a reliable customer support chatbot

Deploy an LLM-powered evaluation system

Construct a clickbait detector from scratch

Understand the challenges of deploying LLMs at scale

Explore privacy and security concerns in LLMs

Learn to test for fairness, bias, and transparency

Overview the most exciting trends in LLMOps

Discuss the role of LLMOps in the MLOps ecosystem

Build a roadmap for the immediate future of LLMs

Module 1. Introduction to LLMs

Brief introduction to LLMs

Explore the importance of LLMOps in LLM engineering

Breakdown the LLMOps lifecycle

Overview the difference between LLMOps and MLOps

Module 2. Working with LLMs

Module 3. LLMOps in Practice

Module 4. Case Studies & Applications of LLMs

Module 5. Advanced Topics in LLMs and LLMOps

Module 6. The Future of LLMOps

An ML Platform Built for Enterprise, Driven by Community

Comet’s ML platform is trusted by innovative data scientists, ML practitioners, and engineers in the most demanding enterprise environments.

"Comet has aided our success with ML and serves to further ML development within Zappos.”

10%

reduction in order returns due to size

Kyle Anderson

Director of Software Engineering

"Comet offers the most complete experiment tracking solution on the market. It’s brought significant value to our business."

Service for millions of customers

Olcay Cirit

Staff Research and Tech Lead

“Comet enables us to speed up research cycles and reliably reproduce and collaborate on our modeling projects. It has become an indispensable part of our ML workflow.”

Developing
NLP tools for thousands of researchers

Victor Sanh

Machine Learning Scientist

"None of the other products have the simplicity, ease of use and feature set that Comet has."

Developing speech and language algorithms

Ronny Huang

Research Scientist

View Case Studies

"After discovering Comet, our deep learning team’s productivity went up. Comet is easy to set up and allows us to move research faster."

Building
speech recognition with deep learning

Guru Rao

Head of AI

"We can seamlessly compare and share experiments, debug and stop underperforming models. Comet has improved our efficiency."

Pioneering family history research

Carol Anderson

Staff Data Scientist

Enterprise User

"Comet has aided our success with ML and serves to further ML development within Zappos.”

10%

reduction in order returns due to size

Kyle Anderson

Director of Software Engineering

Enterprise User

"Comet offers the most complete experiment tracking solution on the market. It’s brought significant value to our business."

Service for millions of customers

Olcay Cirit

Staff Research and Tech Lead

Community User

“Comet enables us to speed up research cycles and reliably reproduce and collaborate on our modeling projects. It has become an indispensable part of our ML workflow.”

Developing
NLP tools for thousands of researchers

Victor Sanh

Machine Learning Scientist

Community User

"None of the other products have the simplicity, ease of use and feature set that Comet has."

Developing speech and language algorithms

Ronny Huang

Research Scientist

View Case Studies

Enterprise User

"After discovering Comet, our deep learning team’s productivity went up. Comet is easy to set up and allows us to move research faster."

Building
speech recognition with deep learning

Guru Rao

Head of AI

Enterprise User

"We can seamlessly compare and share experiments, debug and stop underperforming models. Comet has improved our efficiency."

Pioneering family history research

Carol Anderson

Staff Data Scientist

By the end of this course, you’ll be able to:

Choose and finetune an LLM for your specific needs

Get the most out of an LLM—from prompt engineering to model evaluation

Build LLM-powered applications with vector databases and other tools

Prevent bias in your LLM and combat bad actors

Frequently Asked Questions

What are the prerequisites for this course?

This course assumes no advanced math background. We will not be diving deep into the theory behind LLMs. All you need to get started is some basic proficiency in Python and a general understanding of deep learning.

Will it cost me anything?

The course content is 100% free. OpenAI has been generous enough to provide us with API credits, which we will make available on a first-come, first-serve basis. In addition, all enrollees will have access to Comet ML’s suite of tools.

How much time should I commit?

The course is self-paced, so you can spend as little or as much time as you want. That said, students who set aside a meaningful block of time each week—whatever “meaningful” means for your schedule—tend to see the best results.

How long will this course take?

Your time to completion will vary depending on how much time you have available. In general, we recommend one week per module as a realistic pace for most people, meaning the course would take six weeks total. Of course, you can take as long as you’d like.

Join fellow students to discuss course content or ask questions in the Community Slack

Join the Slack Group

FREE COURSE

LLMOps: Building Real-World Applications With Large Language Models

Expert Instructors

Self-Paced

Built with OpenAI

Course Description

Who is This For?

Why This Course?

Taught By An Expert

What You'll Learn

Module 1. Introduction to LLMs

Module 2. Working with LLMs

Module 3. LLMOps in Practice

Module 4. Case Studies & Applications of LLMs

Module 5. Advanced Topics in LLMs and LLMOps

Module 6. The Future of LLMOps

Module 1. Introduction to LLMs

Module 2. Working with LLMs

Module 3. LLMOps in Practice

Module 4. Case Studies & Applications of LLMs

Module 5. Advanced Topics in LLMs and LLMOps

Module 6. The Future of LLMOps

An ML Platform Built for Enterprise, Driven by Community

Enterprise User

Enterprise User

Community User

Community User

Enterprise User

Enterprise User

By the end of this course, you’ll be able to:

Frequently Asked Questions

What are the prerequisites for this course?

Will it cost me anything?

How much time should I commit?

How long will this course take?

Join fellow students to discuss course content or ask questions in the Community Slack

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