Build Chat Applications with OpenAI and LangChain
Build Chat Applications with OpenAI and LangChain
Gain cutting-edge AI skills: Master the LangChain framework to build and deploy real-world AI applications
Product Brand: Udemy
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Udemy Coupon Code for Build Chat Applications with OpenAI and LangChain Course. Gain cutting-edge AI skills: Master the LangChain framework to build and deploy real-world AI applications.
Created by 365 Careers | 5.5 hours on-demand video | 54 downloadable resources
LangChain Course Overview
Build Chat Applications with OpenAI and LangChain
In this Build Chat Applications with OpenAI and LangChain course, we’ll explore the increasingly popular LangChain Python library to develop engaging chatbot applications.
With detailed, step-by-step guidance, you will use OpenAI’s API key to access their powerful large language models (LLMs). Once we have access to foundational models, we’ll utilize LangChain and its integrations to create compelling prompts, add memory, input external data, and link it to third-party tools.
LangChain’s integration with third-party tools distinguishes it by enabling connections to various language models and loading documents in multiple formats. It also allows for selecting suitable embedding models, storing embeddings in a vector store, and linking to search engines, code interpreters, and tools like Wikipedia, GitHub, Gmail, and more.
None of this would be possible without mastering the LangChain Expression Language (LCEL)—essential for developing stateful, context-aware reasoning chatbots. These chatbots remember past conversations, answer questions about unseen data, and tackle more complex problems.
Additionally, we’ll spend much of our time discussing the state-of-the-art Retrieval Augmented Generation (RAG), both theoretically and practically. This technique allows LLM-powered applications to analyze and answer questions about information outside their training data. Ultimately, we’ll create a chatbot that answers students’ questions on courses from the 365 library.
What you’ll learn
- Master LangChain to seamlessly integrate existing applications with potent Large Language Models (LLMs)
- Learn to connect to OpenAI’s language and embedding models
- Develop prompt engineering skills that improve performance and relevance of AI responses
- Apply the state-of-the-art Retrieval Augmented Generation (RAG) technique to empower your AI-driven product with a knowledge base
- Leverage AI to open up endless opportunities for your organization
- Enhance your career prospects with rare and highly sought-after AI Engineering skills
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Gen AI – RAG Application Development using LangChain Course
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This Gen AI – RAG Application Development using LangChain course on developing RAG Applications using Open AI GPT APIs, LangChain LLM Framework and Vector Databases is intended to enable learners who want to build a solid conceptual and hand-on proficiency to be able to solve any RAG automation projects given to them. This course covers all the basics aspects of LLM and Frameworks like Agents, Tools, Chains, Retrievers, Output Parsers, Loaders and Splitters and so on in a very thorough manner with enough hands-on coding. It also takes a deep dive into concepts of Language Embeddings and Vector Databases to help you develop efficient semantic search and semantic similarity based RAG Applications. We will also cover multiple Prompt Engineering techniques that will make your RAG Applications more efficient.
AI-Agents: Automation & Business with LangChain & LLM Apps Course
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Dive into “AI Agents: Automation & Business through LangChain Apps“—where you will explore the basic and advanced concepts of AI agents and LLMs, their architectures, and practical applications. Transform your understanding and skills to lead in the AI revolution.
Who this course is for:
- Aspiring AI engineers
- Everyone who is serious about integrating AI into their product
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