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Course Recommendation System for Surveys with Data Tables and GPT-4.1-Mini logo

Course Recommendation System for Surveys with Data Tables and GPT-4.1-Mini

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Recommends courses from survey responses using Data Tables and AI.

n8nAI & LLMBeginner👁 66 views
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Updated 2026-06-15

What is the Course Recommendation System for Surveys with Data Tables and GPT-4.1-Mini workflow?

This workflow collects survey responses via a form trigger, stores them in Data Tables alongside course listings, and leverages an AI Agent powered by OpenAI to match respondents with suitable courses based on their answers.

It is designed for educators, course providers, and organizations seeking to automate personalized learning recommendations efficiently.

What it automates

University course matching

After students submit preference surveys, the workflow recommends specific elective courses from the catalog with reasoning tied to their answers.

Corporate training suggestions

HR collects employee skill-gap surveys and automatically recommends relevant internal courses stored in a data table.

Online learning platform personalization

New users fill out interest surveys; the system returns tailored course titles plus short explanations pulled from the course options table.

Apps & integrations used

AI AgentOpenAI Chat ModelStructured Output Parser

How to set up Course Recommendation System for Surveys with Data Tables and GPT-4.1-Mini

  1. 1Open the template in n8n
  2. 2Connect OpenAI credentials for the Chat Model node
  3. 3Set up the two Data Tables (Survey Responses and Course Options)
  4. 4Configure the Form Trigger with your survey fields
  5. 5Adjust the AI Agent prompt if needed for your course data
  6. 6Activate the workflow and test with sample submissions

Course Recommendation System for Surveys with Data Tables and GPT-4.1-Mini: pros & cons

Pros

  • +Uses structured output for reliable recommendations
  • +Keeps data in simple n8n Data Tables
  • +Beginner-friendly with clear node flow
  • +Combines survey input with course catalog automatically

Cons

  • –Requires OpenAI API access and credits
  • –Needs initial population of both Data Tables
  • –Recommendations depend on prompt quality
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Frequently asked questions

It takes survey responses, pulls course options, and uses GPT-4.1-mini via an AI Agent to return structured course recommendations with reasoning.

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