Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
4 Hour(s) 30 Minute(s)
Language
English
Taught by
Markus Lang
Rating
1 views
Course Overview
From the Basics of LLMs to Production-Grade Microservice Architecture with Kubernetes (Latest Version 1.0.x)
This course provides an in-depth exploration into LangChain, a framework pivotal for developing generative AI applications.
Now fully updated for LangChain 1.0.x — including LCEL, LangGraph-based orchestration, the revamped Agents API, and the langchain_classic imports.
Aimed at both beginners and experienced practitioners in the AI world, the course starts with the fundamentals, such as the basic usage of the OpenAI API, progressively delving into the more intricate aspects of LangChain.
You'll learn about the intricacies of input and output mechanisms in LangChain and how to craft effective prompt templates for OpenAI models. The course takes you through the critical components of LangChain, such as Chains, Callbacks, and Memory, teaching you to create interactive and context-aware AI systems.
Midway, the focus shifts to advanced concepts like Retrieval Augmented Generation (RAG) and the creation of Autonomous Agents, enriching your understanding of intelligent system design. Topics like Hybrid Search, Indexing API, and LangSmith will be covered, highlighting their roles in enhancing the efficiency and functionality of AI applications.
Toward the end, the course integrates theory with practical skills, introducing Microservice Architecture in large language model (LLM) applications and the LangChain Expression Language. This ensures not only a theoretical understanding of the concepts but also their practical applications.
This course is tailored for individuals with a foundational knowledge of Python, aiming to build or enhance their expertise in AI. The structured curriculum ensures a comprehensive grasp of LangChain, from basic concepts to complex applications, preparing you for the future of generative AI.
Course Content
- 10 section(s)
- 73 lecture(s)
- Section 1 Before we start...
- Section 2 Preparation
- Section 3 LangChain Basics
- Section 4 Chains - From basic to advanced chains
- Section 5 Callbacks
- Section 6 Memory
- Section 7 OpenAI Function Calling
- Section 8 Retrieval Augmented Generation (RAG)
- Section 9 Agents
- Section 10 Indexing API
What You’ll Learn
- Master LangChain from basics to advanced features
- Understand and implement Retrieval Augmented Generation (RAG) using VectorStores
- Learn about the creation and use of powerful Autonomous Agents.
- Grasp the functionalities and applications of the Indexing API.
- Explore the LangSmith Platform for production ready application
- Learn about Microservice architecture in the context of large language model (LLM) applications.
- Learn about the new LangChain Expression Language with the Runnable Interface
Reviews
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YYurii Kochurovskyi
you rock
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SSerhii Manetskyi
As a principal engineer from the Java world, I can say that the concept of the course is good. I like how the instructor demonstrates the power of LangChain and how to build with it. However, the course is very outdated. The code examples are obsolete, and in most cases I have to rely on the official LangChain documentation to make things work or to use the current library implementation. Getting familiar with the documentation is indeed useful, but my expectation was that the instructor’s code would work and serve as a quick introduction to the topic. Instead, I end up wasting time troubleshooting deprecated code examples, only to eventually turn to the official documentation and implement the solution with the current version of the library. UPDATED: There is one more thing - the code shows the examples with legacy chatgpt models 4x. However, it doesn't work with gpt-5x models that are actual today. This is a main reason of looking into the documentation and searching the solutions in the web.
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NNagalakshmi C K
It’s very easy for learner
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VVaibhav Jain
A little outdated now, but very very helpful in building basics.
