Create a chatbot with LangChain to interface with your private data and documents. Learn from LangChain creator, Harrison Chase.

Learn to use LLMs to enhance search and summarize results, using Cohere Rerank and embeddings for dense retrieval.

Design and execute real-world applications of vector databases. Build efficient, practical applications, including hybrid and multilingual searches.

Learn how to build and use knowledge graph systems to improve your retrieval augmented generation applications. Use Neo4j's query language Cypher to manage and retrieve data.

Improve your RAG system to retrieve diverse data types. Learn to extract and normalize content from a wide variety of document types, such as PDFs, PowerPoints, and HTML files.

Build smarter search and RAG applications for multimodal retrieval and generation.

Optimize the efficiency, security, query processing speed, and cost of your RAG applications.

Build an interactive system for querying video content using multimodal AI

Build an event-driven agentic workflow to process documents and fill forms using RAG and human-in-the-loop feedback.

Learn to build AI agents with long-term memory with LangGraph, using LangMem for memory management.

Turn your GenAI prototype into an automated pipeline using Apache Airflow