Description
LangChain in Action: LLM-Powered Application Development Course This course provides a detailed exploration of LangChain, a framework for developing generative AI applications. This course is initially aimed at beginners and experienced professionals in the world of AI, such as basic usage of the OpenAI API, and then gradually moves into more complex aspects of LangChain. You will learn the intricacies of the input and output mechanisms in LangChain and how to create effective fast patterns for OpenAI models. This course will walk you through the critical components of LangChain, such as chains, callbacks, and storage, and teach you to create interactive and context-aware AI systems. In the middle, the focus shifts to advanced concepts such as Retrieval Augmented Generation (RAG) and the creation of autonomous agents, enriching your understanding of intelligent system design. Topics such as Hybrid Search, Indexing API, and LangSmith are covered, highlighting their role in increasing the efficiency and performance of AI applications. Finally, the course combines 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 the theoretical understanding of the concepts but also their practical application. This course is aimed at people with basic knowledge of Python and aims to build or expand their expertise in the field of artificial intelligence. The structured curriculum ensures a comprehensive understanding of LangChain, from basic concepts to complex applications, and prepares you for the future of productive AI.
What you will learn in the LangChain in Action: Develop LLM-Powered Applications course
-
Master LangChain from basics to advanced features
-
Understanding and implementing Retrieval Augmented Generation (RAG) with VectorStores
-
Learn about creating and using powerful standalone agents.
-
Understand the features and uses of the Indexing API.
-
Discover the LangSmith platform for a production-ready application
-
Learn more about microservice architecture in the context of Large Language Model (LLM) applications.
-
Learn more 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
- Editor: Udemy
- Lecturer: 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-based Applications
LangChain in Action: Course Prerequisites for LLM-Based Application Development
- Intermediate Python knowledge (OOP, data types, functions, modules, etc.)
- Helpful: Terminal and Docker knowledge
Course pictures
Sample video of the course
installation Guide
After extracting, you can watch it with your favorite player.
Subtitles: None
Quality: 720p
Download link
free download software
Size
1.69GB