Coursera Courses, Ratings & Instructors Scraper

Here is one real result, with every field the actor returns (this record has withDetails and all three AI add-ons enabled; the long subtitleLanguages list and description are trimmed with a note, values real):

{
  "imageUrl": "https://s3.amazonaws.com/coursera-course-photos/3c/77927732934dc0a10a44bd3306833d/1200x1200px_1001823008.jpg",
  "title": "Machine Learning with Python",
  "url": "https://www.coursera.org/learn/machine-learning-with-python",
  "id": "course~8UjeMk-mEeit4g4GsxE4dg",
  "productType": "COURSE",
  "partner": "IBM",
  "partners": ["IBM"],
  "partnerLogo": "http://coursera-university-assets.s3.amazonaws.com/bb/f5ced2bdd4437aa79f00eb1bf7fbf0/IBM-Logo-Blk---Square.png",
  "rating": 4.67,
  "reviewCount": 18448,
  "difficultyLevel": "Intermediate",
  "durationCategory": "1 to 3 months",
  "certificateType": "Course Certificate",
  "isFree": false,
  "isPartOfCourseraPlus": true,
  "isCreditEligible": false,
  "tagline": "Offered by IBM",
  "skills": ["Unsupervised Learning", "Supervised Learning", "Model Evaluation", "Regression Analysis", "Scikit Learn (Machine Learning Library)", "Machine Learning Methods", "Applied Machine Learning", "Model Training", "Predictive Modeling", "Machine Learning Algorithms", "Statistical Methods", "Machine Learning", "Dimensionality Reduction", "Python Programming", "Logistic Regression", "Model Optimization", "Classification Algorithms"],
  "tools": null,
  "languages": ["English"],
  "subtitleLanguages": ["Arabic", "Azerbaijani", "Bengali", "Chinese", "Dutch", "French", "German", "..."],
  "enrollmentCount": 703534,
  "instructors": ["Joseph Santarcangelo", "SAEED AGHABOZORGI"],
  "workload": "5-6 weeks of study, 3-6 hours per week",
  "description": "Python is a core skill in machine learning, and this course equips you with the tools to apply it effectively. You'll learn key ML concepts, build models with scikit-learn, and gain hands-on experience using Jupyter Notebooks. ...",
  "aiSummary": "This intermediate course on Machine Learning with Python, offered by IBM, teaches you essential machine learning concepts and techniques using Python and scikit-learn. It's designed for learners who want to deepen their understanding of both supervised and unsupervised learning methods, and by the end, you'll be able to build and evaluate machine learning models confidently, culminating in a final project on rainfall prediction.",
  "aiTags": ["machine learning", "python", "scikit learn", "supervised learning", "unsupervised learning", "model evaluation", "regression", "classification", "dimensionality reduction", "applied machine learning", "predictive modeling", "intermediate course"],
  "aiCategory": {
    "category": "Data Science",
    "subcategory": "Machine Learning",
    "level": "Intermediate"
  },
  "sourceQuery": "machine learning",
  "observedAt": "2026-08-14T07:06:50.486Z",
  "error": null
}

The most complete Coursera catalog scraper available. It returns every field the Coursera search exposes, including rating, review count, skills, partner, difficulty and pricing signals, plus detail-page enrichment (full description, instructors, workload, enrollment count) and three optional AI add-ons, and gives you three filters to target exactly the courses you need.

📥 Input · 📤 Output · 💰 Pricing · ▶️ Examples

Table of contents

• What it does
• Quickstart
• Input reference
• Output reference
• Example output record
• Run via API and CLI
• Fetch results
• Billing and limits
• FAQ and troubleshooting

What it does

The actor searches the public Coursera catalog for each keyword or URL you pass, applies the filters you set, paginates through the matching products, and writes one normalized record per course to the run's dataset. Enum values are turned into readable labels, ratings are rounded, and when withDetails is on the actor opens each product to add the full description, instructor names, workload and total enrollment count. Missing source values are returned as null, never invented.

Data covers the entire public Coursera catalog: individual courses, specializations, professional certificates, guided projects and degrees. Three optional AI add-ons (withAiSummary, withAiTags, withAiCategorize) can enrich each record; they are opt-in, billed only when they produce output, and disabled on free Apify plans.

Quickstart

Open the actor, paste this into the input, and press Run. It returns 2 machine learning courses with detail pages.

{
  "searchQueries": ["machine learning"],
  "maxCourses": 2,
  "withDetails": true
}

Instead of searchQueries, you can pass startUrls (course, specialization or search URLs). Leave the AI add-ons off (default) for the raw course fields.

Input reference

Field	Type	Required	Default	Description
searchQueries	array	no*	(empty)	One or more keywords to search, for example machine learning, python, project management. Each keyword runs its own search.
startUrls	array	no*	(empty)	Coursera course, specialization or search URLs. Product URLs return that single product; search URLs run the keyword behind them.
maxCourses	integer	no	10	Maximum courses to collect across the run. Free Apify plans are capped at 25 per run.
withDetails	boolean	no	true	Open each product to add the full description, instructors, workload and enrollment count.
productType	enum	no	(all)	Restrict to one type: Courses, Specializations, Professional Certificates, Guided Projects, Degrees. Applies to keyword searches.
difficultyLevel	enum	no	(all)	Restrict to one level: Beginner, Intermediate, Advanced, Mixed.
language	enum	no	(all)	Only courses available in this language (audio or subtitles), for example English, Spanish, Portuguese.
withAiSummary	boolean	no	false	Add a plain-English AI summary of each course. Paid add-on, disabled on free plans.
withAiTags	boolean	no	false	Generate concise topic/keyword tags via AI. Paid add-on, disabled on free plans.
withAiCategorize	boolean	no	false	Classify each course into a subject category, subcategory and level via AI. Paid add-on, disabled on free plans.

* Provide at least one searchQueries entry or one startUrls entry.

Output reference

One dataset item per course. Types: string, number, boolean, string[], object, or null when the source value is absent.

Field	Type	Description
imageUrl	string	Course cover image URL.
title	string	Course or program name.
url	string	Direct link to the Coursera product page.
id	string	Coursera product ID.
productType	string	COURSE, SPECIALIZATION, PROFESSIONAL_CERTIFICATE, GUIDED_PROJECT or DEGREE.
partner	string	Primary university or company offering the product.
partners	string[]	Every institution credited on the product.
partnerLogo	string	Logo image of the primary partner.
rating	number	Average learner rating out of 5, or null.
reviewCount	number	Number of ratings behind the score, or null.
difficultyLevel	string	Beginner, Intermediate, Advanced or Mixed.
durationCategory	string	Expected time to complete, for example 1 to 3 months.
certificateType	string	Credential the product awards.
isFree	boolean	Whether the course can be taken free, or null.
isPartOfCourseraPlus	boolean	Whether it is included in a Coursera Plus subscription.
isCreditEligible	boolean	Whether it can count toward academic credit.
tagline	string	Short marketing tagline.
skills	string[]	Skills the course teaches, or null.
tools	string[]	Named software or tools taught, or null.
languages	string[]	Languages with full audio and subtitles.
subtitleLanguages	string[]	Languages available as subtitles only.
enrollmentCount	number	Total learners enrolled. Present with withDetails.
instructors	string[]	Instructor names. Present with withDetails.
workload	string	Recommended study time and length. Present with withDetails.
description	string	Full course description. Present with withDetails.
aiSummary	string	AI plain-English summary. Present only when withAiSummary is enabled.
aiTags	string[]	AI topic tags. Present only when withAiTags is enabled.
aiCategory	object	AI category, subcategory, level. Present only when withAiCategorize is enabled.
sourceQuery	string	The keyword or URL that produced this record.
observedAt	string	ISO 8601 timestamp of when the record was collected.
error	string	null on success. On a failed run, a single item with a populated error field is written instead.

Example output record

Real record from a live run (input {"searchQueries":["machine learning"],"maxCourses":2,"withDetails":true}), with the long description trimmed for readability:

{
  "title": "Machine Learning with Python",
  "url": "https://www.coursera.org/learn/machine-learning-with-python",
  "id": "course~8UjeMk-mEeit4g4GsxE4dg",
  "productType": "COURSE",
  "partner": "IBM",
  "rating": 4.67,
  "reviewCount": 18448,
  "difficultyLevel": "Intermediate",
  "durationCategory": "1 to 3 months",
  "certificateType": "Course Certificate",
  "isFree": false,
  "isPartOfCourseraPlus": true,
  "tagline": "Offered by IBM",
  "languages": ["English"],
  "enrollmentCount": 703534,
  "instructors": ["Joseph Santarcangelo", "SAEED AGHABOZORGI"],
  "workload": "5-6 weeks of study, 3-6 hours per week",
  "description": "Python is a core skill in machine learning, and this course equips you with the tools to apply it effectively. ...",
  "sourceQuery": "machine learning",
  "observedAt": "2026-08-14T07:06:50.486Z",
  "error": null
}

Run via API and CLI

Start a run and wait for it to finish, then read the dataset. Replace <TOKEN> with your Apify API token.

Run synchronously and get dataset items in one call:

curl -X POST "https://api.apify.com/v2/acts/scrapers_lat~coursera-scraper/run-sync-get-dataset-items?token=<TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"searchQueries":["machine learning"],"maxCourses":25,"withDetails":true}'

Start a run asynchronously:

curl -X POST "https://api.apify.com/v2/acts/scrapers_lat~coursera-scraper/runs?token=<TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"searchQueries":["python"],"productType":"Professional Certificates","difficultyLevel":"Beginner","maxCourses":100}'

Apify CLI:

apify call scrapers_lat/coursera-scraper \
  --input '{"startUrls":["https://www.coursera.org/learn/machine-learning-with-python"]}'

Fetch results

Every run writes to a dataset. Fetch items as JSON, CSV, or Excel by changing format:

# JSON
curl "https://api.apify.com/v2/datasets/<DATASET_ID>/items?token=<TOKEN>&clean=true&format=json"

# CSV
curl "https://api.apify.com/v2/datasets/<DATASET_ID>/items?token=<TOKEN>&clean=true&format=csv"

# Paginate large datasets
curl "https://api.apify.com/v2/datasets/<DATASET_ID>/items?token=<TOKEN>&offset=1000&limit=1000"

<DATASET_ID> is returned as defaultDatasetId in the run object. Use offset and limit to page through large result sets. clean=true drops empty and internal fields.

Billing and limits

• Pay per result. You are charged per course returned (result event). See the pricing tab for the current per-result price.
• Detail enrichment billed separately. With withDetails on, a details event is charged per course only when the detail fetch succeeds.
• AI add-ons billed separately. withAiSummary, withAiTags and withAiCategorize each charge their own event only when they produce output, and are disabled on free plans.
• No charge on failure. If a run errors, the actor writes a single item with a populated error field and does not charge for it. Empty runs cost nothing.
• Spend cap respected. Set maxTotalChargeUsd on the run; once reached, the actor stops emitting and charging further billable results.
• Free Apify plans are capped at 25 records per run. Upgrade for higher maxCourses.

FAQ and troubleshooting

A run returned 0 records. Why? The keyword matched nothing under the chosen filters. Loosen productType, difficultyLevel or language, or broaden the keyword. Zero-result runs are not charged.

Can I scrape a specific course instead of searching? Yes. Paste one or more course, specialization or search URLs into startUrls. Product URLs return that single product; a search URL runs the keyword behind it.

Where do enrollment numbers and instructor names come from? enrollmentCount, instructors, description and workload are collected when withDetails is enabled. The listing fields like rating, skills and pricing signals are always included.

Why is a field like workload or rating null? Some products do not expose every field (for example workload on a specialization, or a rating on a brand new course). Missing source values are returned as null, never guessed.

Do the AI add-ons work on a free plan? No. The AI add-ons require a paid Apify plan and are disabled automatically for free users. The base course fields are always returned.

Is this an official Coursera tool? No. This actor is independent and has no affiliation with Coursera. It reads only data that is publicly available on the platform. Use it in accordance with Coursera's terms of service.

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Independent tool, not affiliated with Coursera. Accesses only publicly available course data. Use in accordance with Coursera's terms of service.