Gen AI - LLM RAG Two in One - LangChain + LlamaIndex

About this course

This course leverages the power of both LangChain and LlamaIndex frameworks, along with OpenAI GPT and Google Gemini APIs, and Vector Databases like ChromaDB and Pinecone. It is designed to provide you with a comprehensive understanding of building advanced LLM RAG applications through in-depth conceptual learning and hands-on sessions. The course covers essential aspects of LLM RAG apps, exploring components from both frameworks such as Agents, Tools, Chains, Memory, QueryPipelines, Retrievers, and Query Engines in a clear and concise manner. You'll also delve into Language Embeddings and Vector Databases, enabling you to develop efficient semantic search and similarity-based RAG applications. Additionally, the course covers various Prompt Engineering techniques to enhance the efficiency of your RAG applications.

List of Projects/Hands-on included: Develop a Conversational Memory Chatbot using downloaded web data and Vector DB

Create a CV Upload and Semantic CV Search App Invoice Extraction RAG App

Create a Structured Data Analytics App that uses Natural Language Queries ReAct Agent: Create a Calculator App using a ReAct Agent and ToolsDocument Agent with Dynamic Tools: Create multiple QueryEngineTools dynamically and orchestrate queries through AgentsSequential Query Pipeline: Create Simple Sequential Query PipelinesDAG Pipeline: Develop complex DAG Pipelines

Dataframe Pipeline: Develop complex Dataframe Analysis Pipelines with Pandas Output Parser and Response Synthesizer

Working with SQL Databases: Develop SQL Database ingestion Bot

Create a FAST API for your LangChain Application just

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