Cohort 5

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

Elvis Saravia

LLMs for Everyone

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Amazon

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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.

Effectively prompting and 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.

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 useful and common tasks such as code generation, 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>Familiarize and build with approaches like ReAct, RAG, 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 conversational assistants with external tools and knowledge bases</li></ul>

Develop use cases and build applications

<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>

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 others</li><li>Discuss current trends, papers, and future directions in prompt engineering</li></ul>

Learn prompt engineering tools

Provide a brief description for each module as a way to sell the value of what students will be learning throughout the course.

First Module

Second Module

Third Module

Course syllabus

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What people are saying

Meet your instructor

Live sessions, demos, exercises, and projects

Live Sessions

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

Live Office Hours

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

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.

1-on-1 Sessions

Course schedule

This course builds on live workshops and hands-on projects

Active hands-on learning

You’ll be interacting with other learners through breakout rooms and project teams

Interactive and project-based

Join a community of like-minded people who want to learn and grow alongside you

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