How to scrape free course listings from Reed using the Minexa.ai extension

Here is what the data looks like before you read a single instruction.

[
  {
    "course_title": "Level 2 Certificate in Awareness of Mental Health Problems",
    "provider_name": "Learning Curve Group",
    "enquiry_count": "8,704 enquiries",
    "course_description": "Complete online for FREE when it suits you, with study materials and tutor support.",
    "course_features": "Tutor support",
    "list_item_description": "Regulated qualification",
    "link_href": "/courses/level-2-certificate-in-awareness-of-mental-health-problems/279420#/courses/free",
    "compare_id": "compareCheck279420",
    "dropdown_button_id": "dropdown-toggle-279420"
  },
  {
    "course_title": "Level 2 Certificate in Creating a Business Start-Up",
    "provider_name": "Learning Curve Group",
    "enquiry_count": "11,903 enquiries",
    "course_description": "Complete online for FREE when it suits you, with study materials and tutor support.",
    "course_features": "Tutor support",
    "list_item_description": "Regulated qualification",
    "link_href": "/courses/level-2-certificate-in-creating-a-business-start-up/279097#/courses/free",
    "compare_id": "compareCheck279097",
    "dropdown_button_id": "dropdown-toggle-279097"
  }
]

That output came from Reed's free courses listing page at reed.co.uk/courses/free, extracted using the Minexa.ai Chrome extension with no code written. The rest of this post shows exactly how to get there.

What Reed's free courses page contains

Reed is one of the UK's largest job and learning platforms. Its free courses section lists government-funded and provider-sponsored courses across health, business, technology, and social care. Each card on the listing page carries a course title, a short description, a provider name, a feature tag such as 'Tutor support' or 'Certificate included', an enquiry count, a qualification status label, a cover image, and a share button encoding a JavaScript function call with UTM parameters baked in.

Collecting this data manually, card by card across multiple pages, takes significant time. The Minexa.ai extension handles pagination automatically and returns every field as structured, exportable JSON.

Before jumping into the steps, watch the full walkthrough video below.

https://www.youtube.com/watch?v=q1hAsFbLB0s

Step 1: Install Minexa.ai and open the target page

If you have not installed the extension yet, add it from the Chrome Web Store. Once installed, navigate to reed.co.uk/courses/free and let the page fully load before opening the extension.

The page shows a paginated list of free courses. Minexa.ai will detect this structure automatically once you open the extension popup.

Step 2: Confirm you are on the right page

Click the Minexa.ai icon in your Chrome toolbar. The extension popup opens and displays the detected URL. Click 'I'm on the right page' to confirm and move forward.

This step locks the extension onto the current page structure so it knows what to train the scraper against.

Step 3: Review pagination detection

Minexa.ai scans the page for pagination controls and displays the pages it has found. For the Reed free courses listing, it detects the numbered page navigation at the bottom of the results. Review the list and click Continue.

Automatic pagination means you do not need to manually supply URLs for each page. The extension handles the traversal for you.

Step 4: Choose list-only or list with detail pages

The extension asks whether you want to scrape the listing cards only, or follow each card link and extract data from the individual course detail pages as well. For a broad course catalogue dataset, list-only is the faster option. If you need full course descriptions or module breakdowns, choose list and detail.

For this walkthrough, selecting the list-only option is sufficient to capture all the fields shown in the sample output above.

Step 5: Select simple scraping mode

After choosing your scraping scope, the extension presents a choice between simple and advanced scraping mode. Simple mode works well for standard paginated listings like this one. Advanced mode is available if you need custom click sequences or dynamic interactions before data loads.

Select simple mode and proceed. The extension will move to the container selection step.

Step 6: Highlight the data container

This is the only visual selection step. Hover over the section of the page that contains the full list of course cards. Minexa.ai highlights the container in blue as you move your cursor. Click to confirm the selection. You are selecting the parent wrapper that holds all the cards, not an individual field inside one card.

Once confirmed, click Create Scraper. Minexa.ai analyses the container structure and automatically identifies every data point within it. This takes a minute or two.

Step 7: Review the extracted data points

After the scraper is created, the extension displays all the columns it has discovered. You can use the next and previous navigation to browse through the full set of extracted fields.

For the Reed free courses listing, the fields include course_title, course_description, course_features, provider_name, enquiry_count, list_item_description, compare_id, dropdown_button_id, course_share_button, link_href, image_src, and source_image_srcset.

A few of these fields are worth understanding in more detail.

The course_share_button field captures a JavaScript function call string per card. It encodes the numeric course ID, the full course display name, and a relative path with UTM parameters for medium, campaign, content, and source all in a single parseable value. This makes it straightforward to extract course IDs programmatically without needing to parse the URL separately.

The compare_id field surfaces the checkbox identifier used by Reed's comparison feature. Because this value is unique per course card and tied to the course's numeric ID, it can serve as a reliable deduplication key when merging datasets across multiple scraping runs.

The dropdown_button_id field provides the toggle identifier for the action menu on each card. Like compare_id, it encodes the course ID and can be used to match records across list and detail page extractions.

The source_image_srcset field captures a thumbnail-optimised CDN URL ending in _cover_thumb.webp, which is distinct from the full cover image path returned in image_src. Both point to Reed's resources CDN, but the thumbnail variant is smaller and faster to load, which matters if you are building a course catalogue display or a content enrichment pipeline.

Step 8: Complete configuration and run

The summary screen shows your job configuration and gives you the option to connect a Google Sheet or set up a recurring schedule. Click Complete Configuration to save the job. It will appear at the top of your scraping jobs list.

Click Run to start extraction. The job processes all detected pages and populates the results table in real time.

Step 9: Export your data

Once the job finishes, the full dataset is available in the results table. Export to Excel or JSON depending on your workflow. Each row corresponds to one course card, and each column maps to one of the extracted fields.

If you want to run the same extraction again later, the scraper is saved and reusable. No retraining needed unless Reed changes its page structure.

Ready to try it on Reed or any other education listing? Install the Minexa.ai extension from the Chrome Web Store and run your first extraction in under ten minutes.

For more on scraping education and course data, see the related guide: Scraping scholarship data from Scholarship America with Minexa.ai.