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29 lines
1.3 KiB
Markdown
29 lines
1.3 KiB
Markdown
# Prompt Engineering Course
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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).
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[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.
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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).
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Topics we provide training on:
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- Taxonomy of Prompting Techniques
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- Tactics to Improve Reliability
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- Structuring LLM Outputs
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- Zero-shot Prompting
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- Few-shot In-Context Learning
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- Chain of Thought Prompting
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- Self-Reflection & Self-Consistency
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- ReAcT
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- Retrieval Augmented Generation
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- Fine-Tuning & RLHF
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- Function Calling
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- AI Safety & Moderation
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- LLM-Powered Agents
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- LLM Evaluation
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- Adversarial Prompting (Jailbreaking and Prompt Injections)
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- Judge LLMs
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- Common Real-World Use Cases of LLMs
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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. |