Prompt Engineering for LLMs


(63 ratings)


4 Days


Cohort-based Course

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



Last chance to enroll







Course overview

Effectively prompting and building with LLMs


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 LLM Outputs

• Zero-shot Prompting

• Few-shot In-Context Learning

• Chain of Thought Prompting

• Self-Reflection & Self-Consistency

• ReAcT Prompting Framework

• Retrieval Augmented Generation (RAG)

• Fine-Tuning & RLHF

• Function Calling & Tool Usage

• LLM-Powered Agents

• LLM Evaluation & Judge LLMs

• AI Safety & 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 

... and much more


• 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:


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 for any questions, corporate trainings, and group/student discounts.


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

Who is this course for


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.

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

14 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

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    (63 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.

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    Join an upcoming cohort

    Prompt Engineering for LLMs

    Cohort 9

    $800 USD


    Apr 22—25, 2024

    Payment Deadline

    Apr 21, 2024

    Don't miss out! Enrollment closes in 18 hours


    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.

    Director, Data Science at Guru
            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

      April 22-25 (13:00 - 15:30 PM PST)

      4 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

    • 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
    Join an upcoming cohort

    Prompt Engineering for LLMs

    Cohort 9

    $800 USD


    Apr 22—25, 2024

    Payment Deadline

    Apr 21, 2024

    Don't miss out! Enrollment closes in 18 hours


    Bulk purchases

    $800 USD




    4 Days