Computer Science / LLM (Large Language Model)

Large Language Models: Application through Production

بواسطة: edX

Overview

This course is aimed at developers, data scientists, and engineers looking to build LLM-centric applications with the latest and most popular frameworks. You will use Hugging Face to solve natural language processing (NLP) problems, leverage LangChain to perform complex, multi-stage tasks, and deep-dive into prompt engineering. You will use data embeddings and vector databases to augment LLM pipelines. Additionally, you will fine-tune LLMs with domain-specific data to improve performance and cost, as well as identify the benefits and drawbacks of proprietary models. You will assess societal, safety, and ethical considerations of using LLMs. Finally, you will learn how to deploy your models at scale, leveraging LLMOps best practices.

By the end of this course, you will have built an end-to-end LLM workflow that is ready for production!

Syllabus

Module 1 - Applications with LLMs
Module 2 - Embeddings, Vector Databases and Search
Module 3 - Multi-stage Reasoning
Module 4 - Fine-tuning and Evaluating LLMs
Module 5 - Society and LLMs: Bias and Safety
Module 6 - LLMOps

Taught by

Matei Zaharia, Sam Raymond, Chengyin Eng and Joseph Bradley

Computer Science / LLM (Large Language Model)

Large Language Models: Application through Production

الذهاب الي الدورة

Large Language Models: Application through Production

بواسطة: edX

edX
مجانية
الإنجليزية
متاح شهادة
أيام محددة
intermediate
English

Messages Timeline Exceptions Views14 Route Queries6 Models5 Gate Session Request

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