Generative AI for Javascript Developers - LangChain, RAG
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Welcome to the Generative AI and LangChain Course for JavaScript Developers! This course is tailored specifically for JavaScript professionals ready to advance their careers in the rapidly growing field of generative AI. While AI and machine learning have traditionally been dominated by Python, generative AI has opened up new possibilities, allowing JavaScript developers to build high-quality, LLM powered applications.Who Should Take This Course? This course is designed for developers and architects with JavaScript and Node.js experience who are eager to build applications powered by large language models (LLMs). You’ll learn how to use JavaScript with LangChain to create generative AI applications, mastering core concepts like RAG (retrieval-augmented generation), embeddings, vector databases, and more. By the end, you’ll be equipped to develop robust generative AI applications.Course Journey: We start with setting up the development environment, creating basic applications to explore key frameworks. Then, we’ll dive into advanced topics, building real-world applications with features like retrievable augmented generation and adding conversational layers with chat history.Key Topics Covered:LangChain with JavaScript/TypeScriptLLMs: Working with top providers like AWS Bedrock, GPT, and AnthropicPrompts & PromptTemplatesOutput ParsersChains: Including legacy chains and LCELLLM Parameters: Temp, Top-p, Top-kLangSmithEmbeddings & VectorStores (e.g., Pinecone)RAG (Retrieval Augmentation Generation)Tools: Web crawlers, document loaders, text splittersMemory & Chat HistoryThroughout the course, you’ll engage in hands-on exercises and build real-world projects to reinforce each concept, ensuring a solid foundation in generative AI with JavaScript. By course completion, you’ll be proficient in using LangChain to develop versatile, high-performance LLM applications.What’s Included? This course is also a community experience. With lifetime access, you’ll receive:GitHub repositories with complete course codeAccess to an exclusive Discord community for support and discussion on GenAI topicsFree updates and continuous improvements at no extra costDisclaimers:This is not a beginner course; software engineering experience and some experience in JavaScript are assumed.We will be using the VSCode IDE (though any editor is welcome).Some LLM services may require payment, but we’ll utilize free options whenever possible.The views and opinions expressed here are my own and do not represent those of my employer.
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8About this sectionVideo lesson
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9Introduction to LangchainVideo lesson
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10Prompt TemplateVideo lesson
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11LLM and Output parsersVideo lesson
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12Langchain FrameworkVideo lesson
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13LLM Chain - LegacyVideo lesson
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14LLM Chain - LCELVideo lesson
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15LLM Parameters - temperature, Top p, Top kVideo lesson
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16LLM Parameters - continueVideo lesson
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17LLM modelsVideo lesson
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18Logging and Debugging Langchain AppsVideo lesson
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22About this sectionVideo lesson
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23What is RAG?Video lesson
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24Vector EmbeddingsVideo lesson
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25RAG ArchitectureVideo lesson
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26Building RAG - load documentsVideo lesson
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27Building RAG - chunkingVideo lesson
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28Building RAG - vectorizationVideo lesson
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29Building RAG - retrievalVideo lesson
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30Building RAG - augmentationVideo lesson
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31Building RAG - LLM and output parserVideo lesson
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32Building RAG - ChainVideo lesson
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33Building RAG - ExecuteVideo lesson

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