Description
LangChain in Action: Develop LLM-Powered Applications course. This course provides an in-depth exploration of LangChain, a framework for developing generative AI applications. This course starts out aimed at beginners and experienced professionals in the world of AI, such as basic use of the OpenAI API, and gradually moves into more complex aspects of LangChain. You will learn about the intricacies of the input and output mechanisms in LangChain and how to create effective rapid patterns for OpenAI models. This course takes you through the critical components of LangChain, such as Chains, Callbacks, and Memory, and teaches you to build interactive and context-aware AI systems. Midway through, the focus shifts to advanced concepts such as Retrieval Augmented Generation (RAG) and creating autonomous agents, enriching your understanding of intelligent system design. Topics such as hybrid search, Indexing API and LangSmith will be covered, highlighting their role in increasing the efficiency and performance of AI applications. Finally, the course integrates theory with practical skills and introduces microservice architecture in applications of the Large Language Model (LLM) and the LangChain expression language. This ensures not only theoretical understanding of the concepts but also their practical applications. This course is designed for people with basic knowledge of Python and aims to build or increase their expertise in artificial intelligence. The structured curriculum ensures a comprehensive understanding of LangChain, from basic concepts to complex applications, preparing you for the future of productive AI.
What you will learn in the LangChain in Action: Develop LLM-Powered Applications course
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Master LangChain from basics to advanced features
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Understanding and implementing Retrieval Augmented Generation (RAG) using VectorStores
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Learn about creating and using powerful standalone agents.
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Understand the functions and uses of the Indexing API.
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Explore the LangSmith platform for a production-ready application
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Learn about Microservice Architecture in the context of Large Language Model (LLM) applications.
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Learn about the new LangChain expression language with the Runnable interface
This course is suitable for people who
- Python developers, AI enthusiasts
Course description LangChain in Action: Develop LLM-Powered Applications
- Publisher: Udemy
- teacher: Markus Lang
- Training level: beginner to advanced
- Training duration: 3 hours and 42 minutes
- Number of courses: 61
Course topics LangChain in Action: Develop LLM-Powered Applications
LangChain in Action: Develop LLM-Powered Applications course prerequisites
- Intermediate Python Skills (OOP, Datatypes, Functions, modules etc.)
- Helpful: Terminal and Docker knowledge
Course images
Sample video of the course
Installation guide
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Quality: 720p
download link
File(s) password: www.downloadly.ir
Size
1.69 GB
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