Large Language Models: Application through Production

Übersicht

This course, designed for developers, data scientists, and engineers, focuses on creating applications centered around Large Language Models (LLMs) using cutting-edge frameworks. Participants will engage with Hugging Face for tackling natural language processing (NLP) challenges, utilize LangChain for complex, multi-phase operations, and explore the intricacies of prompt engineering.

The curriculum includes the use of data embeddings and vector databases to enhance LLM pipelines, as well as techniques for fine-tuning LLMs with specific domain data to boost performance and reduce costs. Additionally, the course delves into the benefits and limitations of proprietary models, alongside discussing the societal, safety, and ethical implications of LLM implementation.

Comprehensive training will be provided on deploying models efficiently at scale, incorporating the best practices of LLMOps. Upon completion, participants will have developed a thorough LLM workflow poised for production.

This course is offered by edX, catering to those interested in LLM applications, Prompt Engineering, LangChain, and Vector Databases.

---

Unterrichtet von

Matei Zaharia, Sam Raymond, Chengyin Eng and Joseph Bradley

---

Fachgebiete