Turn course and certification pages into AI study notes in Markdown

If you are studying for a professional certification or building a graduate school knowledge base, your source material is probably trapped in a messy mix of course portals, PDFs, syllabus pages, discussion boards, compendiums, and paid member sites.

I have been testing Web2MD on exactly that kind of material: sommelier study pages, university Canvas modules, and coursework that only loads after login. This use case came up from real paying users too. One converted 41 pages from the GuildSomm sommelier compendium. Others used Web2MD on Canvas course pages and JHU coursework so they could study with NotebookLM and Claude.

The pattern is simple: turn each important course page into clean Markdown, then feed that Markdown into your AI study tool.

That sounds boring until you try doing it by hand. Course pages are full of navigation, sidebars, banners, collapsible sections, footers, tracking scripts, and formatting that gets lost when you copy and paste. AI tools can work with messy input, but they do better when the material is structured.

Web2MD is a Chrome extension that converts the page you are viewing into Markdown in your browser. That browser part matters.

Why Markdown works well for AI study notes

Markdown keeps the structure that matters:

• headings
• bullet lists
• tables
• links
• code snippets
• reading sequences
• definitions
• module titles

For study workflows, that structure is usually more useful than a screenshot or raw copied text. You can ask Claude to make flashcards. You can upload several Markdown files to NotebookLM. You can ask ChatGPT to compare week 3 lecture notes with the assigned reading. You can paste the notes into Cursor if your coursework includes technical material.

A clean Markdown page might look like this:

# Module 4: Sensory analysis of wine

## Learning objectives

By the end of this module, you should be able to:

- Identify primary, secondary, and tertiary aromas
- Explain how acidity affects perceived freshness
- Compare structural markers in cool climate and warm climate wines

## Required reading

1. GuildSomm Compendium: Structure in wine
2. Regional profile: Loire Valley
3. Tasting grid: White wines

## Key terms

- Acidity: The sour or tart component of wine
- Tannin: Phenolic compounds that create drying texture
- Body: The perceived weight of wine on the palate

That is much easier for an AI model to parse than a giant paste that starts with "Skip to content" and includes the entire course navigation menu.

The problem with course pages

Most course and certification content is not a normal public article.

A Canvas course page may only be visible after you log in through your university. A professional certification compendium may sit behind a membership wall. A hospital, law, finance, or security training site may require SSO. Some pages are public, but many of the pages worth studying are not.

That is where server side converters hit a wall.

Jina Reader is useful for public URLs. Firecrawl is strong for crawling public sites and developer workflows. MarkDownload is a solid browser extension for saving pages as Markdown. I use and respect these tools for the right jobs.

But for logged in course pages, the conversion needs to happen where the content is already visible: inside your browser.

Web2MD runs locally in Chrome. If you can view the page in your browser, Web2MD can usually convert it, including pages that a server side reader cannot fetch because it does not have your session cookies or university login.

My test workflow

Here is the workflow I used while testing course and certification pages.

1. Open the course page in Chrome.
2. Make sure the main content is expanded.
3. Click the Web2MD extension.
4. Review the Markdown preview.
5. Check the token count before sending it to an AI tool.
6. Copy, download, or send the Markdown to Claude, ChatGPT, NotebookLM, or Cursor.
7. Save each page with a consistent file name.

For a certification program, I like file names like:

01-orientation.md
02-core-definitions.md
03-tasting-method.md
04-region-burgundy.md
05-region-loire.md
06-practice-questions.md

For a graduate course, I would use:

week-01-syllabus.md
week-02-readings.md
week-03-lecture-notes.md
week-04-assignment-brief.md
week-05-discussion-prompts.md

The boring file naming helps later. If you upload 30 files to NotebookLM or paste several modules into Claude, clear names make it easier to ask questions like "compare week 4 and week 5" or "make a practice exam from the Burgundy and Loire notes."

Example AI study prompt

Once you have Markdown, you can use a prompt like this:

# Study task

Use the course notes below to build a study guide.

## Instructions

- Keep the original module structure.
- Extract all definitions.
- Create 20 flashcards.
- Create 10 practice questions with answers.
- List topics that need outside review.
- Do not add facts that are not in the notes.

## Source notes

[Paste Markdown here]

This is where Web2MD's token counter is useful. Claude, ChatGPT, NotebookLM, and Cursor all have context limits. They are large, but not infinite. Before you paste or send a long course page, Web2MD shows an estimated token count so you can decide whether to send the full page or split it into sections.

For study corpora, I usually prefer smaller chunks. A 900 token lesson page is easy. A 24,000 token compendium section may need to be split by heading so the model can produce better notes.

Why browser side conversion matters for privacy

Course material can be sensitive. It may include your name, grades, instructor comments, unpublished lectures, private discussion posts, or paid certification content.

A server side tool needs the URL or page content to pass through someone else's infrastructure. That can be fine for public articles. It is less comfortable for private coursework.

Web2MD converts in your browser. The extension is designed for local, private page conversion rather than crawling through a remote service. For professionals studying compliance, medicine, finance, law, wine credentials, security certifications, or internal company training, that difference matters.

It also means you do not need an API key to get started. The free tier includes 3 conversions per day. Pro is 9 dollars per month if you need more.

Where Web2MD fits against other tools

I would not say Web2MD replaces every Markdown converter.

Jina Reader is excellent when you have a public URL and want a quick clean read. Firecrawl is better if you are a developer crawling many public pages or building an ingestion pipeline. MarkDownload is a capable Chrome extension for saving web pages as Markdown.

Web2MD is built for a narrower study and AI workflow:

• It runs on the page you are already viewing in Chrome.
• It works on authenticated pages that public readers cannot access.
• It keeps conversion local and private.
• It includes a token counter before you send content to an AI tool.
• It has one click send to AI for tools like ChatGPT, Claude, and Cursor.
• It has a free tier and does not require an API key.

That makes it a good fit for students and professionals who are collecting pages one by one, not running a crawler across the open web.

Limits to know before you start

Web2MD is Chrome only right now. If you live in Safari or Firefox, that is a real limitation.

The free tier is also limited to 3 conversions per day. That is enough to test the workflow or convert a few important pages, but not enough to process a full certification library in one sitting. Pro is 9 dollars per month.

Conversion quality also depends on the page. If a course portal hides content behind tabs, accordions, or lazy loaded sections, open those sections before converting. If a page is mostly a PDF embedded in a viewer, you may need a PDF workflow instead of a web page workflow. If the page has broken HTML, the Markdown may need a quick cleanup pass.

I would rather be clear about that than pretend every page becomes perfect notes with one click. Most normal course pages convert well. Weird portals sometimes need a little prep.

A practical study corpus workflow

For a serious certification or graduate class, I would set up a folder like this:

ai-study-corpus/
  syllabus.md
  module-01-introduction.md
  module-02-core-concepts.md
  module-03-case-study.md
  module-04-practice.md
  glossary.md
  prompts.md

Then I would use Web2MD to convert each page, save the files, and run a weekly AI study session:

# Weekly review prompt

You are helping me study from my own course notes.

Use these files:
- module-01-introduction.md
- module-02-core-concepts.md
- module-03-case-study.md

Create:
- a one page summary
- a glossary
- 25 flashcards
- 10 exam style questions
- a list of weak areas I should review

That workflow is especially useful when the course is cumulative. You are not asking the AI to invent a study guide from the internet. You are giving it your actual course material in a format it can read cleanly.

Try it on one page first

If you are studying for a certification or building an AI study corpus for grad school, start with one page. Pick a dense lesson, compendium entry, or Canvas module. Convert it with Web2MD, check the token count, and paste the Markdown into your AI tool with a specific study prompt.

If the output is useful, repeat the process for the next few pages.

You can try Web2MD at web2md.org. The free tier gives you 3 conversions per day, which is enough to see whether Markdown based AI study notes fit your workflow.