Platform · Udacity

Udacity Data Scraping

Udacity used to price each Nanodegree. Now most of it sits behind one subscription, which changes what there is to collect.

Udacity data scraping covers the public catalogue of courses and programmes. Udacity was acquired by Accenture in 2024 and folded into its learning business. Most content is now subscription-gated, with free introductory courses and some programmes carrying their own fees, so each record carries an access tier rather than assuming a per-course price. Promotional percentages shown on the pricing page are recorded with their windows. Every fee carries its unit, student category and academic year with a reference to the page or PDF it came from, and no student, applicant or login-gated data is ever collected.

When a platform moves from per-item prices to a subscription, old price series end. The change is dated.

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Free pilot on your own Udacity list, returned in 24 hours. No card, no trial clock — and you keep the sample data either way.

udacity_sample.jsonl LIVE FEED

{"access_tier":"subscription","subscription_price":249,"currency":"USD"} {"access_tier":"free","programme_type":"course"} {"model_change_event":"per-programme to subscription","event_date":"as recorded"}

illustrative sample rows · globaltiers, not prices · schema v1.0

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Udacity or its owners. Udacity and related marks belong to their respective owners, used here only to name the publicly accessible source this service collects from.

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Udacity at a glance

How we handle Udacity specifically

Platform-specific handling, not a generic retail template pointed at a different domain.

Platform: Udacity — Accenture, since 2024
Model: Subscription-gated catalogue
Free: Introductory courses
Separate fees: Some programmes, as published
So: access tier, not an assumed price
Promotions: Percentages with windows
Focus: Technology and data programmes
Refresh: Weekly

Platform specifics

Tiers, not prices

These are the reasons a Udacity dataset needs its own handling rather than a shared retail schema.

Access records

Programme pages state what is included in a subscription and what costs extra; both are recorded as published.

access_tier — free, subscription, separate_fee.
subscription_price with currency and country read.
programme_type — course, nanodegree, degree.
model_change_event where pricing structure changes, dated.

History, and what we do not do

Price history

Series from the per-programme era are kept with a model-change marker so they are not compared with subscription prices. See our Pluralsight page.

Fee units

A fee whose unit cannot be determined is marked unresolved rather than guessed, as the education hub describes.

What we do not do

Create accounts or subscribe, copy course content, infer per-course prices from a subscription, or estimate learner numbers.

Scope

What we collect on Udacity, and what we do not

The right column matters more than the left. Anyone can list fields; the limits are what tell you whether the dataset will hold up.

✅ What we collect

Access tier on every record
Subscription prices with country
Programme type recorded
Separate fees where published
Promotions with windows
Model changes dated
Owner recorded
Course metadata as published
Weekly refresh

❌ What we do not, and why

Accounts or subscriptions
Course content copied
Inferred per-course prices
Estimated learner numbers
Revenue estimates

Core Udacity fields

The full dictionary is agreed during scoping. These are the fields specific to this platform.

Field	What it is on this platform
course_id / platform	Stable identity
title / field	As published
access_tier	free, subscription, separate_fee
subscription_price / currency	As shown
country_read	Where prices differ
programme_type	course, nanodegree, degree
duration / effort	As published
promo_pct / promo_window	As shown
model_change_event	Dated
owner	Accenture
observed_at	Timestamp

Use cases

What teams do with Udacity data

Tech catalogue benchmarking

Programmes by field.

Model change tracking

Per-item to subscription.

Corporate learning analysis

Enterprise-owned platforms.

Promotion tracking

Discounts with windows.

The 24-hour sample — run on your sources, not ours

Send us a Udacity item or category list. We run real collection against it and return the output within 24 hours, with the platform-specific fields populated so you can check them yourself rather than take our word for it.

Real extraction from your actual sources
Returned within 24 hours
Coverage and QA note included
You keep the data either way
No card, no trial clock
Named engineer on the call

Get my free sample Book a 20-min scoping call Reply within one business day. Reference calls available under NDA.

How we engage

Three ways to engage us

Same collection pipeline and QA underneath. The difference is who holds the schedule and how the data reaches you.

Managed service (most common)

We own the collection, the QA and the delivery. You receive clean data on a schedule and never touch a scraper.

Dedicated engineer assigned to your account
Site changes fixed by us, not reported to you
Scheduled delivery to your warehouse or S3
Named contact on Slack or email

Best fit: Teams who need the data, not the infrastructure.

API access

The same collection pipeline exposed as an authenticated REST endpoint your systems query directly.

On-demand and scheduled endpoints
Rate limits agreed to your load profile
Sandbox keys for integration testing
Versioned schema with deprecation notice

Best fit: Product and engineering teams building on live data.

One-time or project extraction

A defined pull for a specific question — market sizing, diligence, a pitch, a one-off audit.

Fixed scope agreed in writing upfront
Single delivery with full QA report
Methodology documented for your records
Converts to managed if you want continuity

Best fit: Research, strategy and diligence work with a deadline.

Pricing

Every engagement is quoted individually, because the honest answer depends on your scope: how many sources, how many records, how often, and how the data reaches you. We scope it with you, run a free pilot on your own sources, and then quote a fixed monthly figure — no per-request metering and no overage billing when volumes move. Request a quote and you will have a number after one call.

Udacity is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Udacity data becomes useful when it sits next to the competitor set on one schema, refreshed on one schedule, so a price index or availability comparison is genuinely like-for-like.

That is what education & edtech data covers, and a Udacity-only engagement can be expanded into it without rebuilding. If you already know you need several platforms, start there instead — it is the same pipeline and usually the better scoping conversation.

FAQ

Udacity data scraping: frequently asked questions

Platform-specific questions, including what cannot be collected here.

Most content is subscription-gated now, with some programmes carrying separate fees. We record the tier.

Accenture, since 2024.

Yes, with a model-change marker.

Never.

No.

It depends on catalogue size and refresh.

Talk to us.

See real Udacity data before you commit to anything

Send us an item or category list. We return the output within 24 hours with the platform-specific fields populated.

Get a free sample Talk to an engineer

Free pilot, no card, no obligation. If we cannot collect a field you need on this platform, the sample shows you that too.

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