What you'll learn:
- Generative AI technology and building LLM powered applications
- Langchain with Javascript/Typescript using latest Langchain version (Nov 2025: updated to latest v1.0 version)
- Build RAG application using private data
- Build chatbot application using LLMs
- Working with different LLMs and LLM providers
- Langchain: LCEL, chains, retrievers, splitters, output parsers, chat memory, langsmith
- Solid understand of concepts: embeddings, vector databases, LLM parameters
** Nov 2025 update: This course is updated with the latest langchain version v1.0. Google Gemini free tier support added to the course code, you can now do this course with both OpenAIand Google Gemini with additional lectures on AWS and Anthropic**
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, LLMpowered 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/TypeScript
LLMs: Working with top providers like AWS Bedrock, GPT, and Anthropic
Prompts & PromptTemplates
Output Parsers
Chains: Including legacy chains and LCEL
LLM Parameters: Temp, Top-p, Top-k
LangSmith
Embeddings & VectorStores (e.g., Pinecone)
RAG (Retrieval Augmentation Generation)
Tools: Web crawlers, document loaders, text splitters
Memory & Chat History
Throughout 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 code
Access to an exclusive Discord community for support and discussion on GenAItopics
Free updates and continuous improvements at no extra cost
Disclaimers:
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.
