DeepLearning.AI - Learning Platform

Function-calling and data extraction with LLMs

Learn to apply function-calling to expand LLM and agent application capabilities.

Nexusflow

Agents Embeddings

Multimodal RAG: Chat with Videos

Build an interactive system for querying video content using multimodal AI

Intel

Computer Vision Embeddings MultiModal NLP RAG Search and Retrieval Vector Databases

Quality and Safety for LLM Applications

Learn how to evaluate the safety and security of your LLM applications and protect against risks. Monitor and enhance security measures to safeguard your apps.

WhyLabs

AI Safety Embeddings Evaluation and Monitoring GenAI Applications Vector Databases

Getting Started with Mistral

Explore Mistral's open-source and commercial models, and leverage Mistral's JSON mode to generate structured LLM responses. Use Mistral's API to call user-defined functions for enhanced LLM capabilities.

Mistral AI

Embeddings Generative Models Prompt Engineering RAG

LangChain Chat with Your Data

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

LangChain

Computer Vision Document Processing Embeddings RAG Vector Databases

Knowledge Graphs for RAG

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.

Neo4j

Embeddings GenAI Applications RAG Search and Retrieval Vector Databases

Embedding Models: from Architecture to Implementation

Learn how to build embedding models and how to create effective semantic retrieval systems.

Vectara

Embeddings Search and Retrieval Vector Databases

Large Language Models with Semantic Search

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

Cohere

Embeddings NLP RAG Search and Retrieval Vector Databases

Understanding and Applying Text Embeddings

Learn how to accelerate the application development process with text embeddings for sentence and paragraph meaning.

Google Cloud

Embeddings GenAI Applications NLP RAG Search and Retrieval

Vector Databases: from Embeddings to Applications

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

Weaviate

Embeddings GenAI Applications RAG Search and Retrieval Vector Databases

Advanced Retrieval for AI with Chroma

Learn advanced retrieval techniques to improve the relevancy of retrieved results. Learn to recognize poor query results and use LLMs to improve queries.

Chroma

Embeddings Fine-Tuning GenAI Applications RAG Search and Retrieval

Building Applications with Vector Databases

Learn to build six applications powered by vector databases, including semantic search, retrieval augmented generation (RAG), and anomaly detection.

Pinecone

Anomaly Detection Embeddings MultiModal Vector Databases

Building Multimodal Search and RAG

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

Weaviate

Embeddings MultiModal RAG Search and Retrieval Vector Databases