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
DeepLearning.AI
Skills you'll gain: Retrieval-Augmented Generation, LLM Application, Large Language Modeling, Prompt Engineering, Vector Databases, Embeddings, System Monitoring, Application Security, Fine-tuning, Artificial Intelligence, Model Evaluation
Skills you'll gain: Prompt Engineering, AI Orchestration, AI Workflows, LangChain, Retrieval-Augmented Generation, Agentic Workflows, Tool Calling, LangGraph, LLM Application, Prompt Patterns, Agentic systems, Multimodal Prompts, Model Context Protocol, Generative AI, AI Security, Generative AI Agents, Vector Databases, OpenAI API, AI Integrations, Software Development
Skills you'll gain: Prompt Engineering, LangChain, Retrieval-Augmented Generation, Prompt Patterns, LLM Application, Generative AI, Vector Databases, Generative AI Agents, Tool Calling, Embeddings, AI Workflows, User Interface (UI), AI Integrations, Large Language Modeling, UI Components, Database Systems, Model Evaluation, Data Storage Technologies, Database Management Systems, AI Enablement
Skills you'll gain: Prompt Engineering, Retrieval-Augmented Generation, Prompt Engineering Tools, LLM Application, Generative AI Agents, Large Language Modeling, Generative AI, Tool Calling, Hugging Face, Context Engineering, Embeddings, Agentic systems
Skills you'll gain: Vector Databases, LLM Application, Retrieval-Augmented Generation, Generative AI, Embeddings, Document Management, Fine-tuning, User Interface (UI)
Skills you'll gain: Prompt Engineering, Prompt Patterns, Data Wrangling, Large Language Modeling, LangChain, Retrieval-Augmented Generation, Exploratory Data Analysis, Unsupervised Learning, Generative Model Architectures, PyTorch (Machine Learning Library), ChatGPT, Generative AI, Restful API, Prompt Engineering Tools, LLM Application, Keras (Neural Network Library), Responsible AI, Vector Databases, Fine-tuning, Python Programming
What brings you to Coursera today?
Skills you'll gain: Prompt Engineering, Apache Spark, Large Language Modeling, Retrieval-Augmented Generation, Transfer Learning, Model Evaluation, Computer Vision, PyTorch (Machine Learning Library), Unsupervised Learning, Generative Model Architectures, Generative AI, PySpark, Prompt Engineering Tools, Vision Transformer (ViT), Keras (Neural Network Library), Vector Databases, Fine-tuning, Machine Learning, Python Programming, Data Science
Coursera
Skills you'll gain: Retrieval-Augmented Generation, LLM Application, Data Flow Diagrams (DFDs), Prompt Engineering, AI Integrations, Generative AI, Embeddings, Diagram Design, Large Language Modeling, Vector Databases, Data Pipelines, Applied Machine Learning
Skills you'll gain: LangChain, Prompt Engineering, LLM Application, Large Language Modeling, Retrieval-Augmented Generation, Vector Databases, Tool Calling, Embeddings, OpenAI API, ChatGPT, Google Gemini, AI Workflows, Generative AI Agents, Token Optimization, Agentic Workflows
DeepLearning.AI
Skills you'll gain: Retrieval-Augmented Generation, Multimodal Prompts, LLM Application, Embeddings, Large Language Modeling, Generative AI, Vector Databases, Image Analysis, Applied Machine Learning
DeepLearning.AI
Skills you'll gain: Agentic Workflows, Tool Calling, Generative AI Agents, Retrieval-Augmented Generation, LLM Application, Agentic systems, Debugging, General Science and Research, Document Management
Skills you'll gain: Retrieval-Augmented Generation, Vector Databases, LLM Application, User Interface (UI), Embeddings, Large Language Modeling, UI Components, Performance Tuning
In summary, here are 10 of our most popular rag courses
- Retrieval Augmented Generation (RAG):Â DeepLearning.AI
- IBM RAG and Agentic AI:Â IBM
- RAG for Generative AI Applications:Â IBM
- Fundamentals of AI Agents Using RAG and LangChain:Â IBM
- Project: Generative AI Applications with RAG and LangChain:Â IBM
- IBM Generative AI Engineering:Â IBM
- IBM AI Engineering:Â IBM
- Understand RAG Basics:Â Coursera
- Introduction to Retrieval Augmented Generation (RAG):Â Coursera
- Building Multimodal Search and RAG:Â DeepLearning.AI
