Coursera Courses Catalog Scraper

Coursera Courses Catalog Scraper — Course Catalog, Languages, and Workload

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

{
  "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.

{
  "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?.