Remove Duplicates from Online Course and Training Data
✓ TestedWorks with CSV, Excel, Google Sheets → JSON-LD Schema
By dataclean.to team · 2026-02-12
Course catalogs and training databases accumulate duplicates when the same program is listed across multiple learning platforms, updated for new cohorts without archiving old entries, and cross-listed under different departments or categories. An introductory Python course might appear as 'Python 101', 'Intro to Python Programming', and 'Python Fundamentals (Fall 2025)' in the same catalog. dataclean.to matches course records by comparing titles, instructor names, curriculum outlines, and enrollment data to identify listings that represent the same educational content.
The Problem
Duplicate course records confuse students and distort institutional analytics. Learners searching a course catalog encounter multiple listings for what appears to be the same class, unsure which to enroll in. Enrollment counts split across duplicate entries make it impossible to gauge a course's true popularity or determine whether it meets minimum enrollment thresholds. Training compliance systems with duplicate records may not accurately track which employees have completed required certifications. Revenue reports undercount per-course income when sales are distributed across multiple listings of the same content. Schema.org Course structured data specification
How to Fix It
1
Export course catalog and enrollment data
Pull all course records from your LMS, training platform, and catalog system. Include course title, instructor, description, category, price, enrollment count, start date, and any certification or credit designations.
2
Upload to dataclean.to
Upload the CSV. The tool normalizes course titles by removing cohort identifiers and date suffixes, compares instructor assignments, and clusters listings that share substantial description overlap.
3
Review duplicate course clusters
Examine groups of listings flagged as the same course. The tool distinguishes between true duplicates and intentional variants like different cohorts or updated versions, showing which fields match and where they differ.
4
Merge into canonical course entries
Consolidate confirmed duplicate listings into one record per course. Enrollment counts from all duplicate entries are summed. The most current description, pricing, and instructor information are retained.
5
Export the clean catalog
Download the deduplicated CSV and update your learning management system. Students now see one listing per course with accurate enrollment data and no confusing duplicate entries.
Frequently Asked Questions
How does the tool handle courses offered in multiple semesters?
The tool detects cohort-specific suffixes like dates and semester labels during title normalization. Courses with identical base titles but different semester designations are flagged for review so you can decide whether to merge them into an evergreen listing or keep them as separate cohort records.
Can it identify updated versions of the same course?
Courses with titles like 'Data Science 101 v2' and 'Data Science 101' are flagged as potential duplicates. The tool shows differences in description content so you can determine if the update warrants a separate listing or should replace the old version.
What about self-paced and instructor-led versions of the same course?
These are flagged based on title similarity and description overlap. You can review the cluster and decide whether the delivery format difference justifies separate listings or if they should be merged with a delivery format attribute.
Example: Input → Output
name
email
phone
city
status
Alice Johnson
alice@example.com
+1-555-0101
New York
active
alice johnson
ALICE@EXAMPLE.COM
5550101
new york
Active
Red rows show common data quality issues. dataclean.to normalizes and generates JSON-LD automatically.