Automated Course Recommendation System Using AI and Data Tables - n8n Workflow

Marketing and Training Departments needing personalized learning path suggestions.
Educators who manage large catalogs of n8n templates and courses.
n8n Automation Specialists looking to implement complex AI-driven decision-making within an n8n workflow.
Users seeking advanced examples of integrating n8n Data Tables with the OpenAI n8n node.

This sophisticated n8n workflow solves the common problem of manually matching user needs (captured via a survey) to an extensive catalog of resources. By combining the power of the n8n Data Tables feature with an advanced LangChain AI agent, this solution ensures scalability and high accuracy. The automation starts with an n8n trigger (a user completing a form), stores the data, retrieves the list of available courses, and passes all relevant information to the AI. The AI's decision-making process is standardized by a Structured Output Parser, guaranteeing that the result is instantly formatted into a rich, personalized response displayed back to the user via an n8n Form node. This specific n8n workflow acts as a complete, end-to-end recommendation engine, demonstrating the power of the n8n platform.

1. Trigger Activation: The process begins when a user completes and submits the Survey Submission n8n trigger (a built-in n8n form).


2. Data Storage: The survey responses are immediately routed to the Store Survey Result n8n node, which uses an upsert operation to record the user's data in the Survey Responses n8n Data Table.


3. Course Retrieval: Simultaneously, the n8n workflow uses the Get Available Courses n8n Data Table node to fetch the entire catalog of courses from the separate Courses Data Table.


4. Data Aggregation: The course items are aggregated and formatted into a single string item (via the Aggregate Courses and Convert to Text n8n nodes) to prepare them for the AI prompt.


5. Data Merge: The Combine Results n8n node merges the user's survey answers and the full list of available courses into a single input payload.


6. AI Decision-Making: This combined payload is passed to the Choose Best Course n8n node, an advanced LangChain Agent configured with the OpenAI Chat Model (gpt-4.1-mini). This agent analyzes the user's experience and needs against the available courses within the n8n workflow.


7. Structured Output: A Structured Output Parser n8n node ensures the AI's response adheres strictly to a predefined JSON format (Course name, reasoning, URL).


8. Instant Feedback: Finally, the Form n8n node captures the structured AI output and dynamically generates an HTML response page, providing the user with their personalized course recommendation immediately after filling out the n8n trigger form. This completes the automatic n8n workflow loop.

This n8n workflow utilizes internal n8n features (Data Tables) and external AI services (OpenAI).

1. Import the n8n workflow: Copy the provided JSON code and import it into your n8n instance via the "New" button and selecting "Import from JSON." This n8n template will be ready to configure.


2. Set up OpenAI Credentials: The Choose Best Course n8n node requires valid OpenAI credentials. Go to Settings > Credentials in n8n, add an OpenAI API credential, and ensure your account has access to models like gpt-4.1-mini.


3. Create n8n Data Tables: This n8n workflow relies on two Data Tables (a core n8n feature) to be created within your n8n instance:

1. Activate the Trigger: The Survey Submission n8n trigger is a form. Save the n8n workflow and click the form link provided in the Survey Submission n8n node to test the complete automation. Ensure the n8n node is active.

Survey Submission (n8n Form Trigger): This n8n trigger initiates the entire process upon form completion. It collects user input regarding their name, experience level, and automation needs.
Store Survey Result (n8n Data Table node): Performs an upsert operation on the Survey Responses Data Table to permanently log the user data. Key configuration ensures field mapping between the form and the Data Table columns.
Get Available Courses (n8n Data Table node): Retrieves all records from the separate Courses Data Table, providing the AI agent with the full context of available learning resources in this n8n workflow.
Convert to Text (n8n Set node): Converts the structured list of courses into a readable text string, essential input for the subsequent OpenAI n8n node.
Choose Best Course (LangChain Agent n8n node): The core intelligence of this n8n template. It uses dynamic input combining survey answers and course data, leveraging the specified gpt-4.1-mini model to make the optimal recommendation. This powerful n8n node drives the decision.
Structured Output Parser (LangChain n8n node): Enforces a clean JSON output schema (course, reasoning, url) from the AI, which is crucial for passing structured data to the next n8n node.

• Form (n8n node): The final action n8n node. It uses the AI's structured output variables to generate a custom, dynamic HTML response page displayed to the user immediately, completing the n8n workflow.