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: 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
Skills you'll gain: Vector Databases, LLM Application, Retrieval-Augmented Generation, Generative AI, Embeddings, Document Management, Fine-tuning, User Interface (UI)
What brings you to Coursera today?
Skills you'll gain: Prompt Engineering, Apache Spark, PyTorch (Machine Learning Library), Large Language Modeling, Retrieval-Augmented Generation, Transfer Learning, Model Evaluation, Computer Vision, 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
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
Duke University
Skills you'll gain: Retrieval-Augmented Generation, Vector Databases, Embeddings, OpenAI API, Data Import/Export, Pandas (Python Package), Generative AI, Application Programming Interface (API), Large Language Modeling, Data Processing, Data Management, Python Programming, Machine Learning
Skills you'll gain: Retrieval-Augmented Generation, Vector Databases, LLM Application, User Interface (UI), Embeddings, Large Language Modeling, UI Components, Performance Tuning
DeepLearning.AI
Skills you'll gain: Retrieval-Augmented Generation, LLM Application, LangChain, Large Language Modeling, Embeddings, Prompt Engineering, Query Languages, Vector Databases, Data Storage, Unstructured Data, Graph Theory
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
- IBM Generative AI Engineering:Â IBM
- Project: Generative AI Applications with RAG and LangChain:Â IBM
- IBM AI Engineering:Â IBM
- Introduction to Retrieval Augmented Generation (RAG):Â Coursera
- Building Multimodal Search and RAG:Â DeepLearning.AI
- Introduction to Retrieval Augmented Generation (RAG):Â Duke University
