Prompt Engineering for LLMs

4.4

(73 ratings)

·

4 Days

·

Cohort-based Course

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

TRUSTED BY

Google
Amazon
Microsoft
LinkedIn
Apple

This course is popular

9 people enrolled last week.

Course overview

Effectively prompting and building with LLMs

OVERVIEW OF THE COURSE

LLMs (Large Language Models) show powerful capabilities, but not knowing how to effectively and efficiently use them often leads to reliability and performance issues. Prompt engineering helps to improve discover capabilities, improve reliability, 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 & Self-Consistency

• ReAcT Prompting Framework

• Retrieval Augmented Generation (RAG)

• Fine-Tuning LLMs

• Function Calling & Tool Usage

• LLM-Powered Agents (Agentic Workflows)

• LLM Evaluation & Judge LLMs

• AI Safety & 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 INSTRUCTOR

Elvis, 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 HELPED

This course has helped AI startups freelancers, and professionals at companies like Apple, Microsoft, Google, LinkedIn, Amazon, Coinbase, Asana, Airbnb, Intuit, JPMorgan Chase & Co, and many others.

Who is this course for

01

Developers building applications on top of LLMs

02

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

03

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

What you’ll get out of this course

Design and optimize prompts
  • Learn key elements and tactics for designing effective prompts
  • Design, test, and optimize prompts to improve model performance and reliability for different tasks such as text summarization and information extraction
Build a robust framework to effectively apply advanced prompt engineering techniques
  • 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.)
  • Build with approaches like ReAct, RAG, function calling, and LLM-powered agents
Develop use cases and build applications
  • Develop use cases such as tagging systems, personalized chatbots, evaluation systems, product review analyzers, and more
  • Build advanced applications that involve combining knowledge with conversational assistants and using LLMs with external tools and knowledge
Perform evaluations for your applications
  • Design a robust framework for evaluating and measuring the quality, diversity, safety, and robustness of LLMs
  • Compare prompt engineering, RAG, and fine-tuning
  • Cover safety topics like prompt injection and moderation tools


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

This course includes

6 interactive live sessions

Lifetime access to course materials

5 in-depth lessons

Direct access to instructor

4 projects to apply learnings

Guided feedback & reflection

Private community of peers

Course certificate upon completion

Maven Satisfaction Guarantee

This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.

Course syllabus

Expand all modules
  • Week 1

    Jun 3—Jun 6

    Week dates are set to instructor's time zone

    Events

    • Jun

      3

      Prompt Engineering for LLMs - Session 1

      Mon, Jun 3, 8:00 PM - 10:30 PM UTC

    • Jun

      4

      Prompt Engineering for LLMs - Session 2

      Tue, Jun 4, 8:00 PM - 10:30 PM UTC

    • Jun

      4

      Optional: Prompt Engineering for LLMs - Office Hour 1

      Tue, Jun 4, 10:30 PM - 11:00 PM UTC

    • Jun

      5

      Prompt Engineering for LLMs - Session 3

      Wed, Jun 5, 8:00 PM - 10:30 PM UTC

    • Jun

      5

      Optional: Prompt Engineering for LLMs - Office Hour 2

      Wed, Jun 5, 10:30 PM - 11:00 PM UTC

    • Jun

      6

      Prompt Engineering for LLMs - Session 4

      Thu, Jun 6, 8:00 PM - 10:30 PM UTC

    Modules

    • Session 1 - Structuring Effective Prompts

    • Session 2 - Advanced Prompting & Improving LLM Reliability

    • Session 3 - LLM Evaluation & AI Safety

    • Session 4 - RAG, Finetuning & Prompt Engineering Tools

4.4

(73 ratings)

What students are saying

Meet your instructor

Elvis Saravia

Elvis Saravia

Elvis is a co-founder of DAIR.AI, where he leads all AI research, education, and engineering efforts. His primary interests are training and evaluating large language models and developing applications on top of them. He is the co-creator of the Galactica LLM and was a technical product marketing manager at Meta AI where he supported and advised world-class teams like FAIR, PyTorch, and Papers with Code. Prior to this, he was an education architect at Elastic where he developed technical curriculum and courses.

A pattern of wavy dots
Be the first to know about upcoming cohorts

Prompt Engineering for LLMs

|

Bulk purchases

What people are saying

        In a rapidly evolving LLM landscape, the live nature of the course enables Elvis to expertly tie in the latest developments when answering questions, provide pointers to foremost resources and share his experience working with many of the tools and frameworks out there. You will not want to miss this course!
Yevgeniy S. Meyer, Ph.D.

Yevgeniy S. Meyer, Ph.D.

Chief Scientist at Gretel (gretel.ai)
        Elvis did a great job of exploring lots of different Prompt Engineering topics, showcased numerous use cases. He also provided us with comprehensive notebooks filled with various examples. The teaching style was really approachable and relaxed, which made for some great live discussions. All in all, it was a pretty solid experience.
Miguel Won

Miguel Won

NLP Data Scientist at Axions Portugal
        The course's focus on practical applications, combined with the theoretical underpinnings, makes it a valuable resource for both beginners and experienced data scientists/software engineers.
Yashwanth (Sai) Reddy

Yashwanth (Sai) Reddy

Director, Data Science at Fidelity Investments
        I had a fantastic experience taking Elvis’ Prompt Engineering Class. He is incredibly knowledge and has the ability to distill the latest research on prompt engineering to make it accessible to almost anyone.
Lawrence Wu 

Lawrence Wu 

Principal Data Scientist at UKG

Course schedule

4 Day Intensive
  • Live Sessions

    July 15-18 (13:00 - 15:30 PM PST)

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

  • Live Office Hours

    1 hour

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

  • 1-on-1 Sessions

    30 mins

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

  • Bonus content

    2 hours per week

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

Learning is better with cohorts

Learning is better with cohorts

Active hands-on learning

This course builds on live workshops and hands-on projects

Interactive and project-based

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

Learn with a cohort of peers

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

Frequently Asked Questions

What happens if I can’t make a live session?
What are the prerequisites for this course?
What tools will we use for the course?
A pattern of wavy dots
Be the first to know about upcoming cohorts

Prompt Engineering for LLMs

|

Bulk purchases