Learn how to add videos from Udemy, Coursera, or YouTube to NotebookLM with HoverNotes and turn video content into a powerful AI source for deeper learning.
By HoverNotes Team•12 min read
TL;DR: NotebookLM can only import YouTube videos directly. To add videos from Udemy, Coursera, university portals, or local files, you first need to convert them into notes. Use a tool like HoverNotes to generate detailed, timestamped notes with screenshots from any video. Then, copy-paste these notes into a Google Doc or upload the Markdown file to Drive and add it as a source in NotebookLM.
So, you want to feed a video into NotebookLM, but it’s not on YouTube. It’s a common problem. While NotebookLM’s built-in YouTube feature is a good start, it leaves out a huge world of content from places like Coursera, Udemy, your university's private lecture portal, or even local video files. Manually taking notes is tedious—constantly pausing and playing, while scattered screenshots lose their context.
The fix is simple: instead of uploading the video directly, you capture its content as detailed notes first, and then feed notes to your AI notebook.
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#Your Quick Guide to Using Any Video in NotebookLM
This is where HoverNotes, a Chrome extension that watches videos with you, generates AI notes, and saves them as Markdown, becomes essential. It "watches" any video playing in your browser and pulls out the important information—creating timestamped, visual notes that NotebookLM can easily digest. Unlike tools that only parse transcripts, HoverNotes watches the video frame-by-frame to capture what's actually on screen, including diagrams, code, and demonstrations that transcripts miss.
Suddenly, that dense video lecture is no longer a passive experience. It's an interactive, searchable document you can chat with.
This process also solves a major problem with video learning: retention. People watch but often don't remember. The act of turning a video into notes improves what you retain dramatically before you even get to NotebookLM. By using an AI assistant for this, you can focus on understanding the material, not the busywork of transcription.
This method turns visual information into a structured, actionable format—the core of what makes AI tools so useful.
#Three-Step Workflow from Video to NotebookLM Source
The whole process boils down to three stages. It's a straightforward way to turn any video into a source for your notebook.
Stage
Action
Key Benefit
1. Capture
Use HoverNotes to generate AI notes from any video playing in your browser.
Grabs crucial visual context—like diagrams, charts, or code snippets—that a simple transcript would completely miss.
2. Prepare
Save the generated notes as a Markdown file or copy them straight into a Google Doc.
You get a clean, well-structured document that’s perfectly formatted for NotebookLM to understand.
3. Import
Add the file from your Google Drive or as a text source directly into your NotebookLM notebook.
Your video's content is now fully searchable, interactive, and ready for you to query.
By bridging this gap, you’re not just adding a video; you're making its knowledge a permanent, interactive part of your digital brain.
#Why NotebookLM Needs a Companion for Most Online Videos
NotebookLM is powerful because it lets you chat directly with your sources. Its native integration with Google Drive and YouTube is incredibly useful, but it also highlights a major gap.
The reality is, most high-value educational content isn't on YouTube. It’s on platforms NotebookLM can't touch—think of your courses on Udemy, Coursera, or LinkedIn Learning, not to mention private university lecture portals. This isn't a fault of NotebookLM; it's just the technical reality of how these platforms are built.
So, how do you get all that valuable video knowledge into your AI workspace? You need a way to process it first. HoverNotes is built to be that bridge. As a Chrome extension, it works anywhere there's a video—course platforms, YouTube, even internal training portals. It uses AI to generate notes and saves them as clean Markdown files on your computer. It’s a simple workflow: turn any video into a text-based source that NotebookLM can read. Suddenly, NotebookLM's reach expands from just YouTube to literally any video you can play in your browser.
This process also tackles one of the biggest problems with video learning itself. The very act of creating notes dramatically improves retention, so you’re already getting more value before you even upload the material into your AI workspace.
Just grabbing a transcript from a video misses the point. A wall of text can't capture the complex diagram drawn on a whiteboard, the crucial line of code on the screen, or the specific data chart being explained. Visual context matters.
That’s why you need a tool that doesn’t just listen to the video, but watches it.
HoverNotes is designed to capture that rich visual context by including timestamped screenshots right in your notes. By preparing your source material this way, you're not just feeding NotebookLM a transcript; you're giving it a high-quality, multimedia document it can use to deliver genuinely useful insights from all your video courses.
Once you have the HoverNotes Chrome extension installed, pull up any video you need to learn from—a university lecture, a course on Udemy, or even a video file on your hard drive.
With your video playing, start the extension. This is where you'll see the difference between HoverNotes and a basic transcription tool. The goal isn't just to dump a wall of text. It's to grab the full context—the visuals, the diagrams, the code on screen—that most tools ignore.
HoverNotes doesn't just listen to the audio; it watches the video frame-by-frame, just like a human would. This allows it to generate notes that weave crucial visual elements right alongside the transcribed text.
Here’s an example. The HoverNotes sidebar is running next to a technical video, capturing both the spoken words and the complex formulas shown on screen.
What you end up with is a rich, contextual document that’s a hundred times more useful for a tool like NotebookLM.
You also have fine-grained control. Instead of grabbing the whole screen, the Snip capture lets you select just a specific area—a single formula, a chart, or a snippet of code. For maximum detail, you can dig into techniques for precision video analysis to ensure nothing gets missed.
The notes HoverNotes produces are built for active learning, not passive review. They are designed to be the perfect source material for NotebookLM.
Here’s what makes these notes so powerful:
Timestamped Screenshots: Every screenshot includes a clickable timestamp—one click returns you to that exact moment. This saves hours of rewatching when reviewing tough topics.
Contextual Images: Screenshots appear right where they belong in your notes, providing visual reference as you study.
Markdown Format: Your notes are saved as clean, simple Markdown (.md) files. They open natively in Obsidian, Logseq, or any text editor. You own the files. Move them, back them up, grep them—they're just Markdown. This local-first approach means you own your knowledge forever.
This entire process ensures your final output isn't a flat transcript but a dynamic, visual document ready for deep work inside NotebookLM. For more ideas on leveling up your note-taking, check out these strategies for creating effective AI video notes.
You've used HoverNotes to capture the key information from your video. Now for the final step: getting those notes into NotebookLM where you can start asking questions. It's a straightforward process with two clean options.
This flexibility means you can add any video to NotebookLM with HoverNotes, whether you're all about local files or you live in the cloud.
Your choice comes down to your personal workflow. One route is ideal for people using local Markdown editors like Obsidian, while the other is a universal fix.
For Obsidian Users (The Local-First Method): HoverNotes saves your notes as plain Markdown (.md) files directly to your file system. Simply upload the .md file you want to analyze into Google Drive. Once it's there, add it as a new source in NotebookLM. The benefit is you maintain complete ownership of your data—it’s your knowledge, on your drive. Notes save as .md files directly to your Obsidian vault, no proprietary format or sync service required.
For Google Docs/Notion Users (The Copy-Paste Method): If you don't use a Markdown editor, the process is just as simple. Highlight all the notes in the HoverNotes editor, copy them, and paste them straight into a new Google Doc. All your formatting—headings, bullet points, and embedded screenshots—will transfer over cleanly.
Pro-Tip: Before adding the file as a source, take 30 seconds to add a clear title and a one-sentence summary at the top of your document. This gives NotebookLM crucial context, leading to much sharper answers when you start asking questions.
No matter which path you take, you get a rich, visual document primed for deep analysis. This workflow is similar to how you'd prep notes for any platform. You can explore other strategies for turning a YouTube video to notes to sharpen your process.
By giving the AI a well-structured source, you turn your video content into a powerful, interactive knowledge base you can talk to.
#How to Get the Most From Your Video Notes in NotebookLM
You've turned a video into a queryable source inside NotebookLM. Now you can go way beyond asking for a simple summary. The combination of visual notes, code snippets, and precise timestamps is a powerful advantage.
Instead of asking vague questions, you can get incredibly specific.
The better your source notes, the better NotebookLM's answers. Because your HoverNotes capture is rich with context—screenshots, timestamps, and transcribed text—you can prompt the AI with surgical precision.
Try thinking in these terms:
"Explain the concept illustrated in the screenshot at [timestamp]."
"Based on the code snippet shown on slide 15, what would be the output?"
"Summarize the key differences between the two charts shown in my notes."
Here's a great feature: if your notes came from a video in another language, you can ask questions about the translated content in English. Watch a Korean lecture and get notes in Spanish—the AI handles translation automatically. You've effectively built your own custom, multilingual knowledge base from a single video course.
When you start pulling video content into NotebookLM using HoverNotes, a few practical questions usually pop up. Here are answers to the most common ones.
#Can I use this on private videos, like from my university?
Yes. This is one of the biggest advantages. If a video plays in your Chrome browser while you're logged in, HoverNotes can access and process it.
This unlocks content from password-protected university portals, internal company training sites, and premium course platforms like Coursera or Udemy. As long as you can watch it, you can take notes on it.
It works for those, too. Just drag your local video file (like an .mp4 or .mov) and drop it into an empty Chrome tab.
The video will start playing in the browser. From there, you can use HoverNotes to generate notes just as you would with any online video.
#Will this work if the video is in another language?
Yes. HoverNotes was built with multiple languages in mind. You can watch a lecture in Japanese, for instance, and tell the AI to generate your notes in English.
Once you add those English notes to NotebookLM, you can interact with the content entirely in English. It's an effective way to learn from international sources without a language barrier.
If you have other questions, you'll likely find the answers in our HoverNotes FAQ section.
The timestamp screenshot feature alone saves hours of rewatching. You can try it free—20 minutes of AI credits are included on signup, no credit card required. Even without AI, the distraction-free mode and screenshots are worth it. Confirm current options on the HoverNotes pricing page.
Useful notes should make you do something with the material, not merely store more text. The U.S. Institute of Education Sciences recommends spacing learning over time, combining graphics with verbal explanations, using active retrieval, and asking deep explanatory questions (practice guide). A peer-reviewed review of educational video research also emphasizes signaling important information, splitting lessons into manageable segments, giving learners control, and adding active-learning prompts (review). Applied here, that means pausing at concept boundaries, capturing only the visual evidence you need, writing a question in your own words, and later answering it before replaying the source. These practices are evidence-based; a universal retention percentage for one app or workflow is not.
