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Education data extraction

Courses, prices and enrollments, delivered as clean data.

We collect courses and prices, ratings, enrollments and provider details from public education and e-learning websites.

Built around your subjects and sources, delivered on your schedule.

Get a free sample from your own sources within 24 hours and see the data before you commit.

100% job success10+ years of experience20k+ course studentsWork directly with the founder
courses.csvsample data
Illustrative sample of scraped course listings. Select a course to see its enrollment history.
courseproviderstudentspricestatus
Example U210.5k$199▲ 7.4%
Open Univ48.9k$149unchanged
Tech Inst152.3k$229▲ 2.5%
Open Univ340$99new
Example U3.6k$79delisted
Illustrative data. Select a course to see its enrollment history.

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Rock the Rankings
Iceland Travel
Blue Orange
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Kore Real Estate Group
42matters
Udemy
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Crunch
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Sunday
Wildcat Capital Management
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catchhotels
QAPA
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Luxury Family Rentals
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Velocity by design
Auditi
mxney
What you get

Every field you need from an education source.

These are the usual building blocks. We add or drop fields to fit your project, and the free sample shows exactly what comes back.

Course

What is being taught.

  • course_title
  • subject
  • level
  • language
  • format
  • duration
  • lessons_count
  • description
  • course_url

Price and offers

What it costs.

  • price
  • original_price
  • discount_percent
  • currency
  • free_or_paid
  • certificate_fee
  • offer_ends
  • price_history

Ratings and enrollment

How learners respond.

  • rating
  • review_count
  • enrolled_students
  • rating_breakdown
  • completion_rate
  • bestseller_flag
  • enrollment_history

Provider and instructor

Who offers it. Public details only.

  • provider_name
  • provider_type
  • instructor_name
  • instructor_rating
  • accreditation
  • country
  • website
  • social_links

Schedule and admissions

When it starts, and how to join.

  • start_date
  • end_date
  • application_deadline
  • seats_available
  • tuition
  • entry_requirements
  • delivery_mode
  • location

Source and history

Where each record came from, and how it changed.

  • first_seen
  • last_seen
  • days_listed
  • listing_status
  • source_urls
  • sources_count
  • last_checked
  • duplicate_of

On requestUniversity program lists, tuition and fee tables, school directories, scholarship listings and training calendars, where they are published.

Who uses it

How teams put education data to work.

Course marketplaces and aggregators

Keep catalogs current with courses from many providers, matched to one record per course, with prices and ratings up to date.

Typical refresh: daily

Edtech companies and course creators

Watch competing courses, prices, ratings and enrollments in your subject, and see what launches, gets discounted or stalls.

Typical refresh: daily to weekly

Universities and training providers

Benchmark programs, tuition and intake dates against other institutions, by subject and country.

Typical refresh: weekly

Researchers and analysts

Study how course supply, pricing and demand change over time, from one consistent history instead of screenshots.

Typical refresh: weekly to monthly
Why it is hard

Why education data is harder than it looks.

Course pages are easy to read and hard to compare. These are the five problems we plan for, and how we handle each.

The problem

Prices swing with promotions.

Many course sites run near-constant discounts, so the price you see today may be gone tomorrow, and the "original" price is often a placeholder.

How we handle it

We store the list price and the sale price separately, with a timestamp for each change, so you can tell real price moves from promotions.

The problem

The same course has many titles.

Providers, marketplaces and aggregators list one course with different titles, levels and descriptions.

How we handle it

We match courses by provider, title and instructor, then merge them into one record that keeps every source.

The problem

Counters are not what they seem.

Enrollment and review counts are rounded, hidden or reset, and some sites show "10K+" instead of a number.

How we handle it

We store each counter exactly as published, note when it is rounded, and track changes over time instead of treating one reading as exact.

The problem

Programs are described differently.

Duration, credits, tuition and intake dates are written differently by every school, and often sit in PDFs or on separate pages.

How we handle it

We pull each field into one structure, convert currencies and units where you ask for it, and keep the original text next to the normalized value.

The problem

Sites block and change.

Education sites use bot protection and redesign their pages, and scrapers quietly return half the rows.

How we handle it

Every pipeline is monitored with row-count and field checks. When a site changes or blocks us, we fix it. Maintenance is part of the service.

How it works

From your list of subjects to a live data feed.

Tell us what you need

Share the course or school sites, the subjects and countries, and the fields. A short call or a message is enough.

See a free sample

Within 24 hours of the call, depending on the sources, you get a sample from your own sources. You see the fields, the quality and the refresh rate before you commit.

Pick the schedule

Hourly, daily, weekly or monthly. We scope the price once you have seen the sample.

Receive and rely on it

Data arrives as CSV, JSON, Excel, Google Sheets, Airtable, in your database, through an API or in cloud storage. We monitor it and fix what breaks.

Common questions

Straight answers.

What teams ask before they start.

What education data can you collect?

Course and program listings with titles, prices, ratings, enrollment counts, schedules and provider details. On request we also collect tuition tables, scholarship lists and school directories. Tell us the fields you need and the free sample shows what is possible.

Can you track price and enrollment changes?

Yes. We re-check your sources on a schedule from hourly to monthly and store every change. You get price history, enrollment history and the date a course disappeared, not just a snapshot. A course that disappears is marked delisted. We cannot tell whether the provider unpublished it or only moved the page.

How do you compare courses across providers?

We keep every field as published and add normalized ones, such as price in one currency, duration in hours and level on one scale, so courses can be compared like for like.

Which sites and countries can you cover?

Course marketplaces, university and school websites, training providers and public education registers, in any country and language. If a source is not practical, for example because of heavy blocking, we tell you upfront, before you commit to anything.

Is scraping education websites legal?

We collect publicly available data only, such as the course details, prices and ratings any visitor can see. Rules differ by country and by site, a site's terms may restrict automated access, reviewer and instructor names can be personal data under laws like GDPR, and data about children needs extra care. We flag risky sources and fields before we build. We are not lawyers, so for sensitive uses we recommend checking with your own counsel.

How do I receive the data?

CSV, JSON, Excel, Google Sheets, Airtable, your own database, an API or cloud storage, on a schedule you choose, ready to feed your catalog, app or dashboard.

How much does it cost, and how fast can we start?

Pricing depends on sources, volume and frequency. We scope it after a free discovery call and sample. Most samples are ready within 24 hours of the call, depending on the sources.

Your free education data sample, built on your actual sources.

Tell us the education sites, subjects, countries and fields you need. We reply with a plan and a sample.

Prefer to talk first? Book a call with the founder

Lazar Telebak, founder of REData Analytics

Lazar Telebak

Founder, REData Analytics

You work directly with the person who builds your data feed. In 10+ years he has worked with 500+ startups, agencies and companies, from one-time extractions to long-running systems processing tens of millions of records.

Founder profile on LinkedIn ↗