Gen AI – RAG Application Development using LangChain
Gen AI – RAG Application Development using LangChain
Develop powerful RAG Applications using Open AI GPT APIs, LangChain LLM Framework and Vector Databases
Created by Manas Dasgupta | 8.5 hours on-demand video course
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.
What you’ll learn
- Fundamental of LLM RAG Application Development
- LLM Frameworks with LangChain
- Using Open AI GPT API to develop RAG Applications
- Prompt Engineering Techniques
- Engineering Optimized Prompts for your RAG Application
- LangChain Loaders and Splitters
- Using Chains and LCEL (LangChain Expression Language)
- Using Retreivers, Agents and Tools
- Conversational Memory
- Multiple RAG Projects with various Source Types and Business Use
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Who this course is for:
- Any Software Developer aspiring to use the power of LLMs to infuse Gen AI features in their Project and Products
- Software Developers looking to automate their Software Engineering processes
