The documents here were uploaded by students, and a great many of them belong to the institution that set the assignment. The metadata is collectable; the files are not.
Plans from €169 a month · Free project assessment · Reply within 1 business day
CSV · Excel · JSON · XML · FTP · SFTP · Amazon S3 · Google Cloud
API, JSON feed or CSV, XLSX and JSON files
ScheduleOne-time, monthly, weekly, daily or 3 times a day
Course Hero pages, filters, fields and a schedule
Built, monitored and repaired by our team
API, JSON feed or CSV, XLSX and JSON files
ScrapeIt runs the collection as a managed service. You name the institutions, subjects or courses; we build the pipeline and hand back CSV, JSON, Excel or a push into your warehouse with institutions, course codes and volumes structured.
Cadence is slow by design. Course catalogues and document libraries change on academic terms rather than daily, so termly or monthly collection with change records suits every brief we have seen here.
We collect metadata about the library, not content from it: uploaded documents, their authors and anything identifying a student stay out of the dataset. We collect only publicly available data - everything a visitor can see on Course Hero - and we collect it legally.
Institution records carry the institution name, country, the course codes listed under it and the document counts per course. That is the backbone of any analysis here, and it is metadata about the library rather than content from it.
Course records carry the course code as the institution writes it, the subject area, the document count by type where the platform distinguishes them, and the date range the uploads span.
Document metadata covers the document type, the course it is filed under, the upload period and the page count where shown. Titles are collected where they are descriptive rather than a filename, because a great many are not.
What we do not collect is the document content, the uploader identity or anything that would let a person be identified from an upload. Students uploading their own coursework did not consent to appearing in a commercial dataset.
Every row carries the collection timestamp and the surface it came from, so any figure traces back to the page that produced it.
Institution coverage analysis is the most common output. Which universities are well represented, which are barely present, and how that maps against enrolment gives a picture of where the platform actually has reach, which is different from where it claims to.
Trend analysis needs repeat collection. Document volume per course over successive terms shows which courses are growing, which are being retired and where new subjects are appearing, and none of that exists in a single snapshot.
Textbook association is part of the same public metadata, which makes it possible to connect courses to the textbooks they use. For a publisher that is the most directly commercial cut of this source.
What we decline is worth stating in the proposal rather than the small print: we do not collect uploaded documents, uploader identities or anything that identifies a student. If a brief depends on those, we are the wrong supplier and we will say so on the first call.
Course Hero is a study materials platform. Students upload notes, past assignments, problem sets and solutions, organised by institution and course code, and other students read them. It is one of the largest such libraries and its institution and course structure is unusually well organised.
That structure is the collectable part and it is genuinely useful. Institutions, the course codes taught at each, how many documents exist per course, what subjects they cluster in and how that changes over time is a real dataset about what is actually being studied and where.
The documents themselves are a different matter entirely, and anyone scoping a project here needs to be clear about it before starting rather than after. The files stay out of the dataset, along with anything that identifies the students who uploaded them.
Textbook data belongs to the same public metadata and connects courses to the textbooks they use.
Delivery: CSV, JSON or XLSX files, our API or a JSON feed. MCP server on request.
Full plan detailsClients arrive wanting the documents and leave wanting the metadata, because the metadata is what answers their questions.
The questions are these. Which courses generate the most study material, and at which institutions. How curriculum coverage differs between universities teaching the same subject. Which textbooks and topics dominate a field. Where demand for tutoring or supplementary content concentrates. Every one of those is answerable from institution, course and volume data without touching a single uploaded file.
For an education company planning where to build content, that map is the brief. For a publisher it shows which courses actually use which material. For a university it shows what its own students are circulating, which is occasionally uncomfortable and always informative.
The files themselves answer almost nothing additional, so they stay out of the dataset, and we would rather say that at the scoping call than after the build. Institutions, course codes, document counts and types, subjects and textbook associations carry the whole picture.
Learn how to use web scraping to solve data problems for your organization
Leveraging advances in technology, the AI-powered web scraper has skyrocketed in demand and is helping to expand capabilities by automating tedious daily tasks and speeding up data collection from thousands of websites several times over.
Web scraping is a method of obtaining web data by extracting it from pages of web resources with the help of a program, that is, in automatic mode. It is used to syntactically convert web pages into more usable forms.
If you specialize in machine learning, you need to feed large amounts of data to the algorithms. Web scraping is the easiest and the most efficient method of collecting the data from all over the Internet.
ScrapeIt is a managed extraction company, not a tool you have to learn. Our team builds the pipeline, watches it as the site changes, and repairs it before your coverage map goes stale.
You see a sample first, in your format, over the institutions and subjects you actually care about, so you can confirm the metadata answers your question before anything larger is built.
Still unsure? Write to info@scrapeit.io
No. Uploaded documents, their authors and anything that identifies a student stay out of the dataset, and we say so at the first call rather than after building it. What we collect is the library metadata around them - institutions, course codes, document counts and types per course.
The library metadata, which is what answers the questions people actually have: institutions, the course codes taught at each, document counts and types per course, subject clustering and how all of that changes over terms. No content, no uploader identities, nothing that identifies a student.
Curriculum and coverage mapping. Which courses generate the most material and where, how coverage of the same subject differs between universities, which textbooks and topics dominate a field, and where demand for supplementary content concentrates. For a publisher or an education company that map is the planning document.
Yes. The library metadata is public: institutions, course codes, document counts and types per course, subjects and textbook associations. We collect only publicly available data - everything a visitor can see on Course Hero - and we collect it legally.
Slowly. Course catalogues and document libraries move on academic terms, not days, so termly or monthly with change records suits every brief we have seen. Delivery is CSV, Excel, JSON, JSONLines or XML over FTP, SFTP, Amazon S3, Google Cloud Storage, Dropbox, Google Drive or email, or written straight into your database.
You share your needs, expectations, and desired timeframe. We'll suggest the best solution based on your request and budget.
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
Tell us which sites, which fields and how often. A couple of lines is enough to start.
Course Hero data from €169/month. Free project assessment, reply within 1 business day.