# Brilliant.org Courses Catalog Scraper (`parseforge/brilliant-courses-scraper`) Actor Scrape Brilliant.org STEM courses catalog: course titles, slugs, descriptions, subjects, difficulty, and lesson counts. Export CSV, Excel, JSON, XML. - **URL**: https://apify.com/parseforge/brilliant-courses-scraper.md - **Developed by:** [ParseForge](https://apify.com/parseforge) (community) - **Categories:** Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. Actors are written with capital "A". ## 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. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ![ParseForge Banner](https://github.com/ParseForge/apify-assets/blob/ad35ccc13ddd068b9d6cba33f323962e39aed5b2/banner.jpg?raw=true) ## โœจ Brilliant.org Courses Catalog Scraper > ๐Ÿš€ **Export the Brilliant.org courses catalog - STEM titles, subjects, difficulty, lesson counts - straight to CSV, Excel, JSON.** > ๐Ÿ•’ **Last updated:** 2026-05-26 ยท **๐Ÿ“Š 8 fields** per record ยท Public data from Brilliant.org The Brilliant.org Courses Catalog Scraper turns the public [Brilliant.org](https://brilliant.org/courses/) data into a clean, structured dataset - directly to CSV, Excel, JSON, JSONL, XML, RSS, or HTML. | ๐ŸŽฏ Target Audience | ๐Ÿ’ก Primary Use Cases | |---|---| | ๐Ÿ“Š Data analysts | Bulk export and analysis | | ๐Ÿข Business teams | Lead enrichment, market research | | ๐Ÿค– ML / AI teams | Build training datasets | | ๐Ÿ“ฐ Journalists | Investigative data sourcing | | ๐Ÿง‘โ€๐Ÿ’ป Developers | Mirror upstream data into your DB | | ๐ŸŽ“ Researchers | Academic and policy research | ### ๐Ÿ“‹ What this scraper does - Connects to Brilliant.org's public endpoint. - Walks listings or detail pages, parsing structured data. - Applies filters from the input schema before pushing rows. - Caps free-tier runs at 10 items; paid users can go up to 1,000,000. - Exports clean rows ready for CSV, Excel, JSON, XML, RSS, or HTML. > ๐Ÿ’ก **Why it matters:** Brilliant.org doesn't ship a public bulk-export. This actor closes that gap - one click, one dataset, one schema. ### ๐ŸŽฌ Full Demo _๐Ÿšง Coming soon._ ### โš™๏ธ Input
FieldTypeRequiredDescription
subjectenumNoSubject area or all.
maxItemsintegerNoFree: 10. Paid: up to 1,000,000.
> โš ๏ธ **Good to Know:** Source coverage and field availability depend on what Brilliant.org surfaces publicly at the time of the run. Some fields may be `null` for records where the source omits them. ### ๐Ÿ“Š Output Each record is a flat object. `imageUrl` is always first (when present), `error` is always last. | Field | Type | Description | |---|---|---| | ๐Ÿ–ผ๏ธ Image `imageUrl` | string | - | | ๐Ÿ“Œ Title `title` | string | - | | ๐Ÿ”– Slug `slug` | string | - | | ๐Ÿ”— URL `url` | string | - | | ๐Ÿ—‚๏ธ Subject `subject` | string | - | | ๐Ÿ“ Description `description` | string | - | | ๐Ÿ“Š Difficulty `difficulty` | string | - | | ๐Ÿ•’ Scraped At `scrapedAt` | string | - | | โŒ `error` | string | Set if upstream fetch failed for this record. | ### โœจ Why choose this Actor | โšก | One-click export - no API keys, no scraping code. | | ๐Ÿงน | Clean snake_case fields ready for BI tools. | | ๐Ÿ“ฆ | Direct CSV / Excel / JSON / XML / RSS / HTML export. | | ๐Ÿค | Free tier (10 items) for quick previews. | | ๐Ÿ”Œ | Native Apify integrations: Make, Zapier, Slack, Google Sheets, BigQuery, Snowflake. | | ๐Ÿ›Ÿ | Graceful error handling - bad rows surface as `error` records, not crashes. | ### ๐Ÿ“ˆ How it compares to alternatives | Approach | Setup time | Maintained? | Clean schema? | |---|---|---|---| | Roll your own scraper | hours-days | you maintain it | manual | | Generic web scrapers | minutes | no schema | no | | **This Actor** | seconds | yes | yes | ### ๐Ÿš€ How to use 1. Click **Try for free**. 2. Adjust the input fields (or leave defaults). 3. Click **Start** and download your dataset. ### ๐Ÿ’ผ Business use cases **๐Ÿ“Š Market research.** Pull a bulk snapshot of Brilliant.org's data for a region, category, or query. **๐ŸŽฏ Lead generation.** Use the structured output to feed CRM enrichment or outbound prospecting. **๐Ÿค– Competitive intelligence.** Track Brilliant.org listings or records over time with scheduled runs. **๐Ÿ“ฐ Newsroom workflows.** Reporters can pull a structured dataset for investigative work in seconds. ### ๐Ÿ”Œ Automating Brilliant.org Courses Catalog Scraper - **Make / Zapier**: trigger this actor on a schedule, push results to Airtable, Google Sheets, Slack. - **Cron schedule**: native Apify scheduler - daily, weekly, monthly runs. - **Webhooks**: get a POST to your endpoint when a run finishes. - **Pipe to BigQuery / Snowflake / Postgres**: native Apify integrations. ### ๐ŸŒŸ Beyond business use cases **๐ŸŽ“ Academia.** Build research corpora from Brilliant.org's public data. **๐Ÿงช Personal projects.** Mirror Brilliant.org data into your own dashboard or app. **๐Ÿค Non-profit / civic tech.** Public-interest tooling on top of public data. **๐Ÿงฐ Prototyping.** Spin up a data feed in seconds to test new ideas. ### ๐Ÿค– Ask an AI assistant about this scraper Pop this README into ChatGPT, Claude, or any AI assistant and ask it to map your workflow to the actor's inputs. ### โ“ Frequently Asked Questions **โ“ Is this allowed?** This actor only requests pages that Brilliant.org serves publicly to any browser - no authentication, no paywall bypass. Users are responsible for complying with the source's terms. **โ“ Do I need an API key?** No. Public data only. **โ“ How fast is it?** Most runs finish within seconds to a few minutes depending on `maxItems`. **โ“ Can I schedule runs?** Yes - Apify ships a native cron scheduler. **โ“ What formats can I download?** CSV, Excel, JSON, JSONL, XML, RSS, HTML. **โ“ Are fields ever null?** Yes - when Brilliant.org omits a value for that record. Required fields are populated whenever the source exposes them. **โ“ How is the free tier limited?** 10 items per run on free accounts. **โ“ Will the schema change?** Only additively - we add fields, never remove. **โ“ How do I integrate?** Use Apify webhooks, Make, Zapier, or the REST API. **โ“ Where can I report a bug?** Apify Console > Actor page > Issues tab. ### ๐Ÿ”Œ Integrate with any app Apify ships native integrations with Make, Zapier, Slack, Discord, Google Drive, Google Sheets, Gmail, Airbyte, Keboola, Telegram, GitHub, and any REST API or webhook endpoint. ### ๐Ÿ”— Recommended Actors | Actor | What it does | |---|---| | [ParseForge Alpha Vantage Scraper](https://apify.com/parseforge/alpha-vantage-public-scraper) | Public market data. | | [ParseForge CurseForge Mods Scraper](https://apify.com/parseforge/curseforge-mods-scraper) | Mod metadata. | | [ParseForge Yahoo Finance Scraper](https://apify.com/parseforge) | Equities and indices. | | [ParseForge OurAirports Scraper](https://apify.com/parseforge/ourairports-scraper) | Global airport database. | > ๐Ÿ’ก **Pro Tip:** browse the complete [ParseForge collection](https://apify.com/parseforge) for 900+ production-grade scrapers. --- **Disclaimer:** This actor scrapes only publicly available data. ParseForge is not affiliated with, endorsed by, or sponsored by Brilliant.org. Users are responsible for complying with the source's terms of service and applicable law. [Create a free account w/ $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp). # Actor input Schema ## `subject` (type: `string`): Filter to a subject area or "all". ## `maxItems` (type: `integer`): Free: 10. Paid: up to 1,000,000. ## Actor input object example ```json { "subject": "all", "maxItems": 10 } ```` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("parseforge/brilliant-courses-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "maxItems": 10 } # Run the Actor and wait for it to finish run = client.actor("parseforge/brilliant-courses-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "maxItems": 10 }' | apify call parseforge/brilliant-courses-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parseforge/brilliant-courses-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Brilliant.org Courses Catalog Scraper", "description": "Scrape Brilliant.org STEM courses catalog: course titles, slugs, descriptions, subjects, difficulty, and lesson counts. Export CSV, Excel, JSON, XML.", "version": "0.1", "x-build-id": "64ixCTkbFLe0Yszts" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parseforge~brilliant-courses-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parseforge-brilliant-courses-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parseforge~brilliant-courses-scraper/runs": { "post": { "operationId": "runs-sync-parseforge-brilliant-courses-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parseforge~brilliant-courses-scraper/run-sync": { "post": { "operationId": "run-sync-parseforge-brilliant-courses-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "subject": { "title": "Subject", "enum": [ "all", "math", "data", "programming", "science", "everyday-math", "foundational-math", "advanced-math", "foundational-logic" ], "type": "string", "description": "Filter to a subject area or \"all\".", "default": "all" }, "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 1000000, "type": "integer", "description": "Free: 10. Paid: up to 1,000,000." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```