Prompt-Engineering-Guide/pages/course.en.mdx

# Prompt Engineering Course

Due to high demand, we've partnered with Maven to deliver a new [cohort-based course on Prompt Engineering for LLMs](https://maven.com/dair-ai/prompt-engineering-llms).

[Elvis Saravia](https://www.linkedin.com/in/omarsar/), who has worked at companies like Meta AI and Elastic, and has years of experience in AI and LLMs, will be the instructor for this course.

This technical, hands-on course will cover prompt engineering techniques/tools, use cases, exercises, and projects for effectively working and building with large language models (LLMs).

Topics we provide training on:

- 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
- Retrieval Augmented Generation
- Fine-Tuning & RLHF
- Function Calling
- AI Safety & Moderation
- LLM-Powered Agents
- LLM Evaluation
- Adversarial Prompting (Jailbreaking and Prompt Injections)
- Judge LLMs
- Common Real-World Use Cases of LLMs

Our past learners range from software engineers to AI researchers and practitioners in organizations like Microsoft, Google, Apple, Airbnb, LinkedIn, Amazon, JPMorgan Chase & Co., Asana, Intuit, Fidelity Investments, Coinbase, Guru, and many others.