# Coursera Search Scraper (`piotrv1001/coursera-search-scraper`) Actor

The Coursera Search Scraper extracts course data based on a search query, capturing course names, ratings, review counts, difficulty levels, skills covered, images, and URLs—ideal for education research and course analysis.

- **URL**: https://apify.com/piotrv1001/coursera-search-scraper.md
- **Developed by:** [FalconScrape](https://apify.com/piotrv1001) (community)
- **Categories:** Automation, Developer tools, Other
- **Stats:** 55 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: 1.00 out of 5 stars

## Pricing

$1.00 / 1,000 courses

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

### 🚀 Coursera Search Scraper

Easily extract course data from Coursera search results. The **Coursera Search Scraper** allows you to gather structured course information based on search queries, making it a valuable tool for education research and course analysis.

### ✨ Features

- 📚 **Comprehensive Course Data**: Retrieve course names, ratings, number of reviews, difficulty levels, skills covered, images, and direct URLs.
- 🔍 **Search-Based Extraction**: Provide a search query to extract relevant course listings.
- ⚡ **Fast & Efficient**: Quickly gather course data for market research and education insights.

### 🛠️ How It Works

1. **Enter a Search Query** – Provide a search term to find relevant courses on Coursera.
2. **Run the Scraper** – Start the process and receive structured course data instantly.

### 📊 Sample Output Data

The scraper provides structured JSON output with key course details. Example:

```json
[
    {
        "avgProductRating": 4.625,
        "cobrandingEnabled": false,
        "completions": null,
        "duration": null,
        "id": "s12n~Rs28_Xm9QOC3HdGFkJJsaw",
        "imageUrl": "https://d15cw65ipctsrr.cloudfront.net/81/18ac67ffeb45d6a4fc30093a4ec817/advanced-js-specialisation.jpg",
        "isCourseFree": false,
        "isCreditEligible": false,
        "isNewContent": true,
        "isPartOfCourseraPlus": true,
        "name": "Advanced JavaScript",
        "numProductRatings": 4,
        "parentCourseName": null,
        "parentLessonName": null,
        "partnerLogos": [
            "http://coursera-university-assets.s3.amazonaws.com/40/d548ef33b3401f942edc9c24840b52/social.png"
        ],
        "partners": ["Scrimba"],
        "productDifficultyLevel": "INTERMEDIATE",
        "productDuration": "ONE_TO_THREE_MONTHS",
        "productType": "SPECIALIZATION",
        "skills": [
            "Ajax",
            "Object Oriented Programming (OOP)",
            "Object Oriented Design",
            "Javascript",
            "JSON",
            "Application Programming Interface (API)",
            "Scripting",
            "Scripting Languages",
            "Software Design Patterns",
            "Data Management",
            "Data Structures",
            "Event-Driven Programming",
            "Data Validation",
            "Programming Principles",
            "Debugging"
        ],
        "videosInLesson": null,
        "translatedName": null,
        "translatedSkills": null,
        "translatedParentCourseName": null,
        "translatedParentLessonName": null,
        "url": "https://www.coursera.org/specializations/advanced-javascript"
    },
    {
        "avgProductRating": 4.181818181818182,
        "cobrandingEnabled": null,
        "completions": null,
        "duration": null,
        "id": "course~k1H8fg_yEe6JUQ5ctKUJaQ",
        "imageUrl": "https://s3.amazonaws.com/coursera-course-photos/b6/d57b7e3dcc45f9a0496e698e61b124/Frontend-Development-using-React.png",
        "isCourseFree": false,
        "isCreditEligible": false,
        "isNewContent": false,
        "isPartOfCourseraPlus": true,
        "name": "Frontend Development using React",
        "numProductRatings": 44,
        "parentCourseName": null,
        "parentLessonName": null,
        "partnerLogos": [
            "http://coursera-university-assets.s3.amazonaws.com/57/ffbfe7f4734ca18bf05a41df254dc9/Frame-11-2-.png"
        ],
        "partners": ["Board Infinity"],
        "productDifficultyLevel": "INTERMEDIATE",
        "productDuration": "ONE_TO_FOUR_WEEKS",
        "productType": "COURSE",
        "skills": [
            "Hypertext Markup Language (HTML)",
            "Front-End Web Development",
            "Javascript",
            "Web Design and Development",
            "React.js",
            "JavaScript Frameworks",
            "Cascading Style Sheets (CSS)",
            "Programming Principles",
            "UI Components"
        ],
        "url": "/learn/frontend-development-using-react",
        "videosInLesson": null,
        "translatedName": null,
        "translatedSkills": null,
        "translatedParentCourseName": null,
        "translatedParentLessonName": null
    }
]
```

Discover and analyze courses efficiently with **Coursera Search Scraper** today! 🚀

# Actor input Schema

## `query` (type: `string`):

Add the search term to find courses on Coursera.

## `limit` (type: `integer`):

Add the number of records you want to scrape.

## Actor input object example

```json
{
  "query": "Frontend"
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "query": "Frontend"
};

// Run the Actor and wait for it to finish
const run = await client.actor("piotrv1001/coursera-search-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "query": "Frontend" }

# Run the Actor and wait for it to finish
run = client.actor("piotrv1001/coursera-search-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "query": "Frontend"
}' |
apify call piotrv1001/coursera-search-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,piotrv1001/coursera-search-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/iw6DPjVZc0NkvXTrl/builds/4zUjbCAyFwio2pXr8/openapi.json