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Certification

Certification in Building and Automating Practical RAG AI Agents with n8n

Become certified in building practical RAG AI agents and automated workflows with n8n. Demonstrate skill in data ingestion, workflow automation, and deploying AI solutions that deliver accurate, data-driven answers for real-world needs.

Exam of 10 to 20 questionsCertificate for LinkedInIntermediate

The exam

Take the certification exam

Multiple-choice questions about the course. Pass with 70% or more and your certificate is issued at once, with a public page and an "Add to LinkedIn" button.

What the exam covers

2 questions from each of the 15 chapters of the course

20 multiple-choice questions, drawn fresh for every attempt. Pass with 70% or more.

  1. 01Masterclass intro3:34
  2. 02Demonstrating RAG2:53
  3. 03Easy drag-and-drop RAG6:07
  4. 04RAG agent with simple vector store12:25
  5. 05Upgrade to Supabase8:46
  6. 06Record manager pipeline17:09
  7. 07Metadata filtering10:25
  8. 08Different file formats8:09
  9. 09OCR for PDFs9:09
  10. 10Handling file deletions3:15
  11. 11Web scraping with Firecrawl17:27
  12. 12Hybrid search21:07
  13. 13Reranking with Cohere5:24
  14. 14Contextual embeddings11:34
  15. 15Agentic RAG, CAG and late chunking4:02
About the course

The "Build Practical RAG AI Agents and Workflows with n8n Automation" certification empowers you to create AI agents that deliver precise answers using your own data through advanced automation. Gain hands-on expertise in n8n for workflow automation, robust data ingestion, and developing reliable, real-world Retrieval Augmented Generation (RAG) systems,skills that boost productivity, adaptability, and your career potential. Enroll now to master in-demand techniques for building scalable AI solutions with confidence.

This certification covers the following topics:

  • Core principles of Retrieval Augmented Generation (RAG)
  • Designing and automating data ingestion pipelines in n8n
  • Handling diverse file types and integrating OCR for PDFs
  • Text chunking strategies for optimal retrieval
  • Generating and storing vector embeddings with Superbase and alternatives
  • Managing duplicate documents with record management techniques
  • Configuring triggers such as Google Drive integration and web scraping
  • Leveraging metadata for precise information retrieval
  • Querying vector stores and transforming questions into grounded answers
  • Prompt engineering for accurate and rule-based AI responses
  • Implementing advanced RAG techniques: hybrid search, re-ranking, and contextual retrieval
  • Building robust, automated AI workflows and addressing real-world challenges

Jobs this certification suits

Our AI checked this certification against 500 jobs; these get the most out of it. Each job links to its learning path.