We extract university profiles, course specifics, tuition fees, and entry requirements from FindAMasters. Delivered as clean JSON, CSV, or Parquet to S3.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Course Details objects from findamasters.com. All fields typed and schema-versioned.
"course_id": "c19482", "title": "MSc Data Science", "university": "University of Bristol", "qualification": "MSc", "duration": "1 year", "study_mode": "Full time"
| # | course_id | title | university | department | qualification | duration |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Fees & Funding objects from findamasters.com. All fields typed and schema-versioned.
"course_id": "c19482", "fee_domestic": 11500, "fee_international": 28900, "currency": "GBP", "fee_year": "2024", "funding_available": true
| # | course_id | fee_domestic | fee_international | currency | fee_year | funding_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Entry Requirements objects from findamasters.com. All fields typed and schema-versioned.
"course_id": "c19482", "degree_requirement": "Computer Science or Mathematics", "grade_requirement": "2:1 honours degree", "ielts_overall": 6.5, "ielts_elements": 6.0, "interview_required": false
| # | course_id | degree_requirement | grade_requirement | english_language | ielts_overall | ielts_elements |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for University Profiles objects from findamasters.com. All fields typed and schema-versioned.
"university_id": "u492", "name": "University of Bristol", "country": "United Kingdom", "city": "Bristol", "world_ranking": 55, "total_students": 27000
| # | university_id | name | country | city | world_ranking | total_students |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Department Data objects from findamasters.com. All fields typed and schema-versioned.
"department_id": "d1029", "university_id": "u492", "name": "School of Computer Science", "faculty_count": 85, "research_rating": "REF 2021 Top 10", "contact_email": "comp-sci@bristol.ac.uk"
| # | department_id | university_id | name | faculty_count | research_rating | contact_email |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our FindAMasters scraper extracts complete course catalogues, normalises tuition fees, and maps university departments across global regions.
Title, qualification type, duration, study mode, and start dates extracted for every listed postgraduate programme.
Domestic and international tuition fees extracted and converted into numeric values with currency codes.
Degree prerequisites, grade minimums, and IELTS/TOEFL score requirements captured as structured fields.
Link courses to specific universities and departments, capturing institutional metadata and location data.
Identify courses with available scholarships, grants, and specific funding flags.
Capture campus locations, city, and country data for geographical distribution analysis.
Categorise programmes by full time, part time, distance learning, or blended study options.
Hash-based diffing identifies new courses, removed programmes, and fee changes between crawl runs.
Extract data across all supported countries and regions listed on the platform.
Brief in. Clean data out.
Provide target countries, subject areas, or specific university IDs. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, pagination logic, and data normalisation rules for findamasters.com.
Schema validation, null-rate checks, and fee outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or warehouse on an agreed cadence.
Higher education directories present complex nested data and inconsistent formatting. Here is how we maintain reliable output.
FindAMasters caps search result visibility. We use granular search facets and category iteration to bypass display limits and ensure 100% catalogue coverage.
Course fees and entry requirements are often free text. Our pipeline uses regex and NLP classifiers to extract numeric values, currencies, and standard grade formats.
Directory layouts vary by university tier. We deploy fallback selector chains to handle sponsored listings, premium profiles, and standard course pages without breaking.
We route requests through residential IPs with realistic browser fingerprints to prevent rate limiting during full catalogue extractions.
We maintain a hash index of last-seen values per course. Subsequent runs only push diffs, allowing you to track fee increases and new programme launches precisely.
Universities monitor competing programmes to align tuition fees, course structures, and entry requirements.
Service providers identify departmental contacts and faculty sizes to target academic software sales.
Analysts track the growth of specific subject areas, like Data Science or AI, across different geographical regions.
Agencies ingest course catalogues to power internal search tools and advise prospective international students.
Higher education consultants analyse domestic versus international fee disparities to advise on pricing models.
Institutions identify universities with complementary departments to propose joint degree programmes or research initiatives.
"FindAMasters aggregates the largest catalogue of postgraduate degrees globally. Querying this data reveals macro trends in higher education pricing and demand."
Extracting higher education data requires precise normalisation. Course fees, durations, and entry requirements vary wildly in format. DataFlirt handles the extraction, standardisation, and pipeline maintenance so your team receives clean, queryable records.
Everything supported by our findamasters.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and deduplication. Playwright handles JavaScript rendering for dynamic course tabs.
Pools of residential ISP proxies ensure high success rates and prevent IP blocking during full directory sweeps.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About findamasters.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We extract both fee types where listed and normalise the text strings into numeric values and standard currency codes.
We typically run FindAMasters extractions on a weekly or monthly cadence, which aligns with the frequency of university updates. Daily runs are available upon request.
Yes. We extract the required degree classification, specific subject prerequisites, and language requirements like IELTS or TOEFL scores.
Yes. Our change detection system uses hash-based diffing to identify new course IDs and flag them in the output payload.
We extract publicly listed department emails, phone numbers, and website URLs associated with the course or university profile.
We extract only publicly accessible directory information. We do not bypass authentication walls or extract personal applicant data.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of UK courses or continuous monitoring of global postgraduate fees, we build and operate the pipeline.
