Retrieval-Augmented Generation (RAG) Courses
Retrieval-augmented generation (RAG) courses can help you learn how to combine information retrieval with generative models, enhancing the quality of AI outputs. You’ll explore techniques for integrating external knowledge sources, fine-tuning models for specific tasks, and evaluating the effectiveness of generated content.
Popular RAG Courses and Certifications
Status: NewSkills you'll gain: Retrieval-Augmented Generation, Database Management Systems, Python Programming, Analysis, Data Import/Export
Status: Free TrialSkills you'll gain: Prompt Engineering, Retrieval-Augmented Generation, LLM Application, LangChain, Large Language Modeling, Vector Databases, Model Deployment, OpenAI API, Hugging Face, Scalability, Embeddings, Generative AI, Data Integration, Data Science, Machine Learning
Status: FreeDeepLearning.AI
Skills you'll gain: Retrieval-Augmented Generation, Vector Databases, Anomaly Detection, Embeddings, LLM Application, Generative AI, Semantic Web, Application Design, Natural Language Processing, Image Analysis, AI Personalization
Status: FreeDeepLearning.AI
Skills you'll gain: Embeddings, Retrieval-Augmented Generation, Large Language Modeling, Semantic Web, Vector Databases, Natural Language Processing
Status: FreeDeepLearning.AI
Skills you'll gain: Full-Stack Web Development, Retrieval-Augmented Generation, Web Applications, JavaScript Frameworks, React.js, LLM Application, Web Development, Javascript, Tool Calling, Generative AI Agents, Data Persistence, Query Languages
Status: Free TrialSkills you'll gain: Large Language Modeling, Retrieval-Augmented Generation, LLM Application, Embeddings, Agentic systems, Application Development, Data Pipelines, Data Integration, Development Environment
Status: NewSkills you'll gain: Retrieval-Augmented Generation, Vector Databases, Embeddings, Tool Calling, AI Workflows, Generative AI Agents, Document Management, Query Languages, Text Mining, Context Management
Skills you'll gain: Retrieval-Augmented Generation, Gemini, Generative AI, Vector Databases, Embeddings
Skills you'll gain: Data Persistence, Retrieval-Augmented Generation, LLM Application, OpenAI API, Full-Stack Web Development, Restful API, Development Environment, Vector Databases, Embeddings, Application Deployment, JSON, Data Integration
Status: FreeDeepLearning.AI
Skills you'll gain: Embeddings, Retrieval-Augmented Generation, Vector Databases, Text Mining, Large Language Modeling, Performance Tuning
Status: Free TrialSkills you'll gain: Retrieval-Augmented Generation, Development Environment, Multimodal Prompts, Embeddings, User Interface (UI), Generative AI, LLM Application, AI Personalization, Image Analysis, Vector Databases
Status: FreeDeepLearning.AI
Skills you'll gain: Retrieval-Augmented Generation, Vector Databases, Prompt Engineering, MongoDB, Query Languages, Metadata Management, Performance Tuning, Embeddings, Data Pipelines
In summary, here are 10 of our most popular rag courses
- Neo4j: Cypher, GDS, GraphQL, LLM, Knowledge Graphs for RAG: Packt
- LLM Engineering with RAG: Optimizing AI Solutions: Coursera
- Building Applications with Vector Databases: DeepLearning.AI
- Embedding Models: From Architecture to Implementation: DeepLearning.AI
- JavaScript RAG Web Apps with LlamaIndex: DeepLearning.AI
- Gen AI - RAG Application Development using LlamaIndex: Packt
- Gen AI - RAG Application Development using LangChain: Packt
- Criar embeddings, pesquisa vetorial e RAG com o BigQuery: Google Cloud
- Developing RAG Apps with LlamaIndex and JS: Packt
- Retrieval Optimization: Tokenization to Vector Quantization: DeepLearning.AI
