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Cohort 5

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Cohort 2

For beginners who want to learn how to apply the latest prompt engineering techniques for LLMs.

Cohort 3 - Beginners

For advanced participants with basic knowledge of machine learning, LLMs, and Python.

Cohort 4 - Intermediate to Advanced

Cohort 3

Cohort 1

Cohort 9

Cohort 4

Cohort 13

Cohort 10

Cohort 6

Cohort 12

Learn to build and deploy effective AI Agents.

Use advanced prompting techniques and tools to improve the capabilities, performance, and reliability of LLM-powered applications

Elvis Saravia

Advanced Prompt Engineering for LLMs

Lead Data Scientist

Software Engineer - Generative AI

Director

Data Scientist

Senior Software Engineer

Research Director

Learn to apply the latest prompting techniques and tools to build use cases and applications with LLMs.

LLMs for Everyone

Business Development

Lead Product Manager

VP M&A

Associate Director

OVERVIEW OF THE COURSELLMs (Large Language Models) show powerful capabilities, but not knowing how to effectively and efficiently use them often leads to reliability and performance issues.&nbsp;Prompt engineering helps to improve discover capabilities, improve reliability,&nbsp;reduce failure cases, and save on computing costs when building with LLMs. This is a hands-on, technical course that teaches how to effectively build with LLMs. It covers the latest prompting techniques (e.g., fe-shot, chain-of-thought, RAG, prompt chaining) that you can apply to a variety of complex use cases such as building personalized chatbots, LLM-powered agents, prompt injection detectors, LLM-powered evaluators, and much more. Topics include: • Taxonomy of Prompting Techniques• Tactics to Improve Reliability• Structuring Inputs and LLM Outputs• Zero-shot/Few-shot/Many-Shot Prompting• Chain of Thought Prompting• Self-Reflection &amp; Self-Consistency• Meta Prompting &amp; Automatic Prompt Engineering• ReAcT Prompting Framework• Retrieval Augmented Generation (RAG)• Fine-Tuning LLMs• Function Calling &amp; Tool Usage• LLM-Powered Agents (Agentic Workflows)• LLM Evaluation &amp; Judge LLMs• AI Safety &amp; Moderation Tools• Adversarial Prompting (Jailbreaking and Prompt Injections)• Common Real-World Use Cases of LLMs• Overview of LLM Tools... and much more PREREQUISITES• This is a technical course and you need to be knowledgeable in Python to take this course.• Basic knowledge of LLMs is beneficial but not required. If you don't have experience using Python, we recommend our beginner's course: https://maven.com/dair-ai/llms-for-everyone ABOUT THE INSTRUCTORElvis, the instructor for this course, has vast experience doing research and building with LLMs and Generative AI. He is a co-creator of the Galactica LLM and author of the popular Prompt Engineering Guide. He has worked with world-class AI teams like Papers with Code, PyTorch, FAIR, Meta AI, Elastic, and many other AI startups. Reach out to training@dair.ai for any questions, corporate trainings, and group/student discounts. WHO THE COURSE HAS HELPEDThis course has helped AI startups freelancers, and professionals at companies like Apple, Microsoft, Google, LinkedIn, Amazon, Coinbase, Asana, Airbnb, Intuit, JPMorgan Chase &amp; Co, and many others.

Effectively prompting and building with LLMs

Course syllabus

4 live sessions (includes lectures, demos, exercises, and projects)

Live Sessions

Optional office hours to ask questions and receive guidance related to the course topics

Live Office Hours

Book a free 1-on-1 session with the instructor to further discuss careers, products, use cases, or anything related to building with LLMs.

1-on-1 Sessions

Includes additional readings and self-paced tutorials + bonus exercises to practice prompt engineering techniques and tools for different use cases and applications

Bonus content

Course schedule

Developers building applications on top of LLMs

Builders wanting to improve LLM reliability, efficiency, and performance for their LLM-powered applications.

Professionals interested in leveling up on how to better use and apply LLMs.

Who is this course for

What you’ll get out of this course

<ul><li>Learn key elements and tactics for designing effective prompts</li><li>Design, test, and optimize prompts to improve model performance and reliability for different tasks such as text summarization and information extraction</li></ul>

Design and optimize prompts

<ul><li>Review and apply the latest and most advanced prompt engineering techniques (few-shot learning, chain-of-thought, RAG, prompt chaining, self-consistency, self-verification, etc.)</li><li>Build with approaches like ReAct, RAG, function calling, and LLM-powered agents</li></ul>

Build a robust framework to effectively apply advanced prompt engineering techniques

<ul><li>Develop use cases such as tagging systems, personalized chatbots, evaluation systems, product review analyzers, and more</li><li>Build advanced applications that involve combining knowledge with conversational assistants and using LLMs with external tools and knowledge</li></ul>

Develop use cases and build applications

<ul><li>Design a robust framework for evaluating and measuring the quality, diversity, safety, and robustness of LLMs</li><li>Compare prompt engineering, RAG, and fine-tuning</li><li>Cover safety topics like prompt injection and moderation tools</li></ul>

Perform evaluations for your applications

<ul><li>Review the latest prompt engineering and LLM tools such as ChatGPT, Llama Index, Comet, LangChain, Flowise, Scale AI's Spellbook, and many more</li><li>Discuss current trends, papers, and future directions in prompt engineering</li></ul>

Learn prompt engineering tools

OVERVIEW OF THE COURSELLMs (Large Language Models) show powerful capabilities, but not knowing how to effectively and efficiently use them often leads to reliability and poor performance.&nbsp;Prompt engineering helps to improve discover capabilities, improve reliability,&nbsp;reduce failure cases, and save on computing costs when building with LLMs. This hands-on course expands your prompting skills to effectively use and build with LLMs. It covers the latest prompting techniques (e.g., few-shot, chain-of-thought, RAG, prompt chaining) that you can apply to a variety of complex use cases such as building personalized chatbots, LLM-powered agents, prompt injection detectors, LLM-powered evaluators, and much more. Topics include: • Taxonomy of Prompting Techniques• Tactics to Improve Reliability• Structuring LLM Outputs• Zero-shot Prompting• Few-shot In-Context Learning• Chain of Thought Prompting• Self-Reflection &amp; Self-Consistency• ReAcT Prompting Framework• Retrieval Augmented Generation (RAG)• Fine-Tuning &amp; RLHF• Function Calling &amp; Tool Usage• LLM-Powered Agents• LLM Evaluation &amp; Judge LLMs• AI Safety &amp; Moderation Tools• Adversarial Prompting (Jailbreaking and Prompt Injections)• Common Real-World Use Cases of LLMs• Prompt Engineering for models like GPT-3.5/4, Mixtral, Gemini, and others&nbsp;... and much more PREREQUISITES• We will explore and build with no-code tools.• No knowledge of programming is required.• Basic knowledge of LLMs is beneficial but not required. If you have experience using Python, we recommend our advanced course: https://maven.com/dair-ai/prompt-engineering-llms ABOUT THE INSTRUCTORElvis, the instructor for this course, has vast experience doing research and building with LLMs and Generative AI. He is a co-creator of the Galactica LLM and author of the popular Prompt Engineering Guide. He has worked with world-class AI teams like Papers with Code, PyTorch, FAIR, Meta AI, Elastic, and many other AI startups. Reach out to training@dair.ai for any questions, corporate training, and group/student discounts. WHO THE COURSE HAS HELPEDThis course has helped AI startups freelancers, and professionals at companies like Microsoft, Google, LinkedIn, Amazon, Coinbase, Asana, Airbnb, Intuit, JPMorgan Chase &amp; Co, and many others.

Live sessions, demos, exercises, and projects

Bonus Content

Book a free 1-on-1 session with the instructor to further discuss careers, products, use cases, or anything related to building with LLMs.

Professionals who want to explore and build with LLMs.

Developers who want to improve LLM reliability, efficiency, and performance for their use cases and applications.

Leaders who want to lead their teams to build innovative products with LLMs.

<ul><li>Learn key elements and tactics for designing effective prompts</li><li>Design, test, and optimize prompts to improve model performance and reliability for useful and common tasks such as code generation, text summarization, and information extraction</li></ul>

<ul><li>Review and apply the latest and most advanced prompt engineering techniques (few-shot learning, chain-of-thought, RAG, prompt chaining, self-consistency, self-verification, etc.)</li><li>Familiarize and build with approaches like ReAct, RAG, and LLM-powered agents.</li></ul>

<ul><li>Develop use cases such as tagging systems, personalized chatbots, evaluation systems, product review analyzers, and more</li><li>Build advanced applications that involve combining conversational assistants with external tools and knowledge bases</li></ul>

<ul><li>Design a framework for evaluating and measuring the quality, diversity, safety, and robustness of LLMs</li><li>Compare prompt engineering, RAG, and fine-tuning</li><li>Cover AI safety topics like prompt injection and moderation tools</li></ul>

<ul><li>Review the latest prompt engineering and LLM tools such as ChatGPT, Llama Index, Comet, LangChain, Flowise, Scale AI's Spellbook, and others</li><li>Discuss current trends, papers, and future directions in prompt engineering</li></ul>

Building Advanced Applications with LLMs

Founder & Lead AI Scientist @ DAIR.AI | Prev: Meta AI, Galactica LLM, Elastic
 

Learn advanced prompting techniques like chain-of-thought and few-shot learning for building LLM applications

Getting Started

Familiarize yourself with tools like Flowise AI and LangChain for building applications with LLMs

The Tools

Bringing everything together to effectively build applications that combine LLMs with external tools and data sources

Learn directly from DAIR AI

DAIR AI

Courses

Advanced Prompt Engineering for LLMs

LLMs for Everyone

Lightning Lessons

Building Advanced Applications with LLMs