LangChain JS – Practical Guide for Javascript Developers | Udemy


LangChain JS – Practical Guide for Javascript Developers | Udemy [Update 09/2024]
English | Size: 1.4 GB
Genre: eLearning

Getting Started with LangChain for Javascript

What you’ll learn
How to Design powerful prompts to query A.I models
How to ntegrate with powerful models like Gemini models from Google and GPT models from OpenAI
Build conversational chat interactions with A.I models
Use A.I to process images
Load data from local files or specific web pages
Generate results based on information from the web and PDF files

The sole purpose of this course is to get your feet wet and your hands building with LangChainJS

LangChainJS gives Web and JavaScript Developers to ability to add A.I-powered features to their web applications using best-in-class Large Language Models from OpenAI, Google, Anthropic and many more LLM vendors out there.

This is the perfect course to get yourself into A.I Engineering and A.I development with LangChain, the biggest A.I software development toolchain in the market today.

By the end of this course, you will have the skills to:

  • Design powerful prompts to query A.I models
  • Integrate with powerful models like Gemini 1.5 Flash from Google Generative AI and GPT 4o by OpenAI
  • Build conversational chat interactions with A.I models
  • Use A.I to process images
  • Control the creativity of the model and how much tokens it consumes
  • Track token consumption
  • Load data from local files or specific web pages
  • Generate results based on information from the web
  • Generate results based on information from your PDF files

So, if anything in the above list sounds fun, let’s get started.

Also, feel free to inbox me about any new chapter you will like me to work on. I’ll appreciate your suggestions

Who this course is for:

  • Web Developers who want to add AI-powered features to their applications
  • Developers who want to transition into A.I Engineering
  • Developers who want to improve the performance of model-powered features with private data
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