# Coursera Extractor (`jupri/coursera`) Actor 💫 All-In-One Coursera.com Scraper - **URL**: https://apify.com/jupri/coursera.md - **Developed by:** [cat](https://apify.com/jupri) (community) - **Categories:** Social media - **Stats:** 32 total users, 0 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing $30.00/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period. You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#rental-actors ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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. - **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use). - **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`. - **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`. - **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`. - **Any other language** — 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 ## 💫 Welcome To Coursera Scraper ![don't be sad readme is here](https://raw.githubusercontent.com/JupriGH/resources/main/cats/catframe.png) ### About Coursera.com **Coursera Inc.** ([/kərˈsɛrə/](https://en.wikipedia.org/wiki/Help:IPA/English "Help:IPA/English")) is an American global [massive open online course](https://en.wikipedia.org/wiki/Massive_open_online_course "Massive open online course") provider. It was founded in 2012[\[2\]](https://en.wikipedia.org/wiki/Coursera#cite_note-2)[\[3\]](https://en.wikipedia.org/wiki/Coursera#cite_note-3) by [Stanford University](https://en.wikipedia.org/wiki/Stanford_University "Stanford University") computer science professors [Andrew Ng](https://en.wikipedia.org/wiki/Andrew_Ng "Andrew Ng") and [Daphne Koller](https://en.wikipedia.org/wiki/Daphne_Koller "Daphne Koller").[\[4\]](https://en.wikipedia.org/wiki/Coursera#cite_note-4) Coursera works with universities and other organizations to offer online courses, certifications, and degrees in a variety of subjects. On February 2, 2021, Coursera announced its [B Corporation certification](https://en.wikipedia.org/wiki/B_Corporation_\(certification\) "B Corporation (certification)") from [B Lab](https://en.wikipedia.org/wiki/B_Lab "B Lab")[\[5\]](https://en.wikipedia.org/wiki/Coursera#cite_note-5) and its transformation into a Public Benefit Corporation.[\[6\]](https://en.wikipedia.org/wiki/Coursera#cite_note-6) As of 2023, more than 300 universities and companies[\[7\]](https://en.wikipedia.org/wiki/Coursera#cite_note-7) were offering courses through Coursera, and by 2024, the number of courses available had risen to approximately 7,000.[\[8\]](https://en.wikipedia.org/wiki/Coursera#cite_note-8) ### About This Actor 💫 **All-In-One Coursera.com Scraper** ***Supported `URL` :*** - https://www.coursera.org/search - https://www.coursera.org/learn/ - https://www.coursera.org/projects/ - https://www.coursera.org/specializations/ - https://www.coursera.org/professional-certificates/ - https://www.coursera.org/instructor/ - https://www.coursera.org/partners/ # Actor input Schema ## `query` (type: `array`): 💡 List of KEYWORDS or URL ## `limit` (type: `integer`): 💡 Number of results (per-query) ## `filters.sort` (type: `string`): No description ## `filters.topic` (type: `array`): No description ## `filters.language` (type: `array`): 💡 The language used throughout the course, in both instruction and assessments. ## `filters.types` (type: `array`): No description ## `filters.level` (type: `array`): No description ## `filters.duration` (type: `array`): No description ## `filters.skills` (type: `array`): No description ## `filters.subtitle` (type: `array`): No description ## `filters.partners` (type: `array`): No description ## `dev_proxy_config` (type: `object`): 💡 Supported protocol:

HTTP(S), SOCKS5
{http|socks5}://{user:pass}@{hostname|ip-address}:port

Example: socks5://example.com:9000 ## `dev_custom_headers` (type: `array`): 💡 Additional HTTP Headers ## `dev_custom_cookies` (type: `array`): 💡 Additional HTTP Cookies ## `dev_transform_fields` (type: `array`): 💡 Transform the resulting output. Select only needed fields.

For nested object use DOT. For example: 
address.streetAddress

For nested array use NUMBER (index of array element starting from index=0). For example: 
images.0.url
## `dev_dataset_name` (type: `string`): 💡 Save results into custom named Dataset, use mask to customize dataset name

{ACTOR} = actor name
{DATE} = date (YYYYMMDD)
{TIME} = time (HHMMSS)

This masks can be used to autogenerate Dataset Name.

example: data-{DATE}
Depending on today date the dataset name will be: data-20230603

default: data-{ACTOR}-{DATE}-{TIME} ## `dev_dataset_clear` (type: `boolean`): Clear Dataset before insert/update. ## `dev_no_strip` (type: `boolean`): 💡 Keep/Save empty values (NULL, FALSE, empty ARRAY, empty OBJECT, empty STRING) ## Actor input object example ```json { "query": [ "python" ], "limit": 5 } ``` # 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 = { "query": [ "python" ], "limit": 5 }; // Run the Actor and wait for it to finish const run = await client.actor("jupri/coursera").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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "query": ["python"], "limit": 5, } # Run the Actor and wait for it to finish run = client.actor("jupri/coursera").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": [ "python" ], "limit": 5 }' | apify call jupri/coursera --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,jupri/coursera" } } } ``` 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 ` 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/B7Thk6C84oy5GdXRF/builds/cTQddbxF0GJI2IGq5/openapi.json