# Coursera Courses Catalog Scraper (`zerobreak/coursera-courses-catalog-scraper`) Actor

Coursera Courses Catalog Scraper is a Python tool designed to extract course titles, instructors, syllabi, ratings, and skill tags from Coursera. It exports structured educational datasets into clean CSV or JSON formats for curriculum research and edtech analysis.

- **URL**: https://apify.com/zerobreak/coursera-courses-catalog-scraper.md
- **Developed by:** [ZeroBreak](https://apify.com/zerobreak) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.99 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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 Courses Catalog Scraper — Course Catalog, Languages, and Workload

![Coursera Courses Catalog Scraper cover](https://images.bigibyte.com/cdn-cgi/image/width=1260,height=540,fit=cover,format=webp/apify-actors-covers/coursera-courses-catalog-scraper-cover.png)

### Overview

Coursera Courses Catalog Scraper collects publicly available course catalog records and organizes them into a structured dataset for research, analysis, and reporting.

The actor supports catalog collection, configurable record limits, and optional local filtering by course name, slug, or description. Results can be exported as JSON, CSV, Excel, or other supported dataset formats.

### Features

- **Course Catalog Collection:** Collect course records from the available catalog.
- **Keyword Filtering:** Filter collected courses by matching text in course names, slugs, or descriptions.
- **Course Metadata:** Extract course identifiers, names, types, descriptions, and slugs.
- **Workload Information:** Collect available course workload estimates.
- **Language Information:** Identify the primary languages associated with courses.
- **Partner Information:** Collect associated partner identifiers when available.
- **Configurable Record Limit:** Set the maximum number of course records to collect.
- **Structured Exports:** Prepare collected records for spreadsheet analysis and data processing.

### Use Cases

- **Catalog Inventory:** Build structured lists of courses and their associated metadata.
- **Topic Research:** Filter courses by keywords relevant to a subject or industry.
- **Workload Analysis:** Compare available workload estimates across courses.
- **Language Research:** Review primary language information for catalog entries.
- **Partner Analysis:** Organize course records by associated partner identifiers.
- **Catalog Snapshots:** Collect datasets periodically to compare catalog information over time.

### Collection Mode

The actor supports the `catalog` mode, which collects course records and applies the configured item limit.

### Input Parameters

| Parameter | Type | Default | Description |
|---|---|---|---|
| `mode` | String | `catalog` | Collection mode. |
| `query` | String | Empty | Optional local text filter matching course names, slugs, or descriptions. |
| `maxItems` | Integer | `50` | Maximum number of course records to collect. |
| `requestDelaySecs` | Number | `1` | Configured delay between requests, in seconds. |
| `timeoutSecs` | Integer | `300` | Overall run time limit, in seconds. |
| `requestTimeoutSecs` | Integer | `30` | Maximum waiting time for an individual request, in seconds. |

### Example Input

```json
{
  "mode": "catalog",
  "query": "",
  "maxItems": 50,
  "requestDelaySecs": 1,
  "timeoutSecs": 300,
  "requestTimeoutSecs": 30
}
```

### What Data Does This Actor Extract?

Each collected course is stored as a structured dataset record. Available fields depend on the information provided for each course.

#### Extracted Data Fields

| Field | Type | Description |
|---|---|---|
| `courseId` | String | Unique course identifier. |
| `courseName` | String | Course title. |
| `courseType` | String | Course type classification. |
| `slug` | String | Slug identifying the catalog entry. |
| `courseDescription` | String | Course description or summary. |
| `workload` | String | Estimated course workload, when available. |
| `primaryLanguages` | Array | Primary languages associated with the course. |
| `partnerIds` | Array | Identifiers of associated course partners. |
| `scrapedAt` | String | Timestamp when the record was collected. |

### Example Output

The following is an illustrative course record.

```json
{
  "courseId": "l31la3mKEe-zFg7heHyXOQ",
  "courseType": "v2.ondemand",
  "courseDescription": "This is a self-paced lab that takes place in the Google Cloud console.",
  "slug": "googlecloud-getting-started-with-the-vertex-ai-gemini-1-5-pro-model-i43mr",
  "workload": "1 hour 30 minutes",
  "primaryLanguages": [
    "en"
  ],
  "partnerIds": [
    "443"
  ],
  "courseName": "Getting started with the Vertex AI Gemini 1.5 Pro Model",
  "scrapedAt": "2026-10-26T00:00:00+00:00"
}
```

Actual values and available fields may vary between course records.

### Working with Your Dataset

After collection, review the dataset and export your results in the format best suited to your workflow.

- **JSON:** Process structured course records in applications and scripts.
- **CSV:** Analyze and filter course information in spreadsheet software.
- **Excel:** Compare course names, workloads, languages, and partner identifiers.

You can also compare datasets from separate runs to review changes in collected catalog records.

### Important Notes

- The `query` parameter filters catalog records locally; it does not perform a remote keyword search.
- Filtering uses available course name, slug, and description text.
- The `maxItems` parameter controls the maximum number of course records collected.
- Some fields may be missing or empty depending on the course record.
- Collected information reflects the catalog data available during the run.

### FAQ

**Who is this actor for?**

It is useful for analysts, researchers, marketers, and developers who need structured course catalog information.

**Can I filter courses by keyword?**

Yes. Set `query` to filter records by matching course names, slugs, or descriptions.

**Does the query perform a remote course search?**

No. The actor filters catalog records locally after collecting them.

**Can I export the results to Excel?**

Yes. The dataset can be exported as Excel, CSV, JSON, and other supported formats.

**Can I collect a limited number of courses?**

Yes. Set `maxItems` to specify the maximum number of records to collect.

### Disclaimer

This actor is an independent tool and is not affiliated with, endorsed by, sponsored by, or officially associated with Coursera or its owners. Users are responsible for ensuring that their collection and use of data comply with applicable laws and relevant terms.

### Is Web Scraping Legal?

Collecting information that is already public is generally legal. There is no single law that bans all forms of web scraping. The limits are the usual ones: do not break into accounts, do not take private or confidential data, and be careful with personal data and copyrighted works. A site's terms can also restrict how you access it. Facts such as a public name, price, or rating are not the same thing as republishing someone's article or photo.

This actor collects information from public pages. It does not log in and it does not bypass access controls.

For a longer explanation, see Apify's article [Is web scraping legal?](https://blog.apify.com/is-web-scraping-legal/).

# Actor input Schema

## `mode` (type: `string`):

What to scrape. Catalog pages the public courses.v1 endpoint.

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

Optional local filter applied to course name, slug, and description (case-insensitive substring).

## `maxItems` (type: `integer`):

Stop after this many successful rows. Hard max is 1000.

## `requestDelaySecs` (type: `number`):

Seconds to wait between requests.

## `userAgent` (type: `string`):

User-Agent header sent with each request.

## `timeoutSecs` (type: `integer`):

Overall run budget in seconds.

## `requestTimeoutSecs` (type: `integer`):

Per-request timeout in seconds.

## `proxyConfiguration` (type: `object`):

Optional proxy. Leave off unless you need it.

## Actor input object example

```json
{
  "mode": "catalog",
  "query": "",
  "maxItems": 100,
  "requestDelaySecs": 1,
  "userAgent": "ActorResearch/1.0",
  "timeoutSecs": 300,
  "requestTimeoutSecs": 30,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

## `overview` (type: `string`):

Dataset rows in the overview table.

## `dataset` (type: `string`):

Full dataset for this run.

## `items` (type: `string`):

Dataset items as JSON.

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("zerobreak/coursera-courses-catalog-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 = {}

# Run the Actor and wait for it to finish
run = client.actor("zerobreak/coursera-courses-catalog-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 '{}' |
apify call zerobreak/coursera-courses-catalog-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,zerobreak/coursera-courses-catalog-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/X4C7MPppr7PEE3ujc/builds/GjLPDtjgONRPFH5IH/openapi.json