OneRange

NotebookLM for Knowledge Work

This course shows how to turn your own documents into a grounded, queryable knowledge assistant with NotebookLM. Learners upload sources, run grounded Q&A, generate summaries and briefings, and create audio overviews while understanding the tool's limits. They leave able to make internal knowledge instantly searchable.

What this course covers

The course runs across 6 topics, each one a short adaptive session rather than a recorded lecture. The tutor explains the idea, works an example, checks understanding, and adjusts the next step to the answer given.

  • Introduction to NotebookLM and Source Uploading — Understand the core value of a grounded AI assistant. Practice creating a notebook and uploading various source types (PDFs, Google Docs, copied text, and URLs) to establish a secure, private knowledge base.
  • Mastering Grounded Q&A and Source Citations — Learn how to query your uploaded documents. Practice writing effective prompts, analyzing the AI's responses, and verifying information using the tool's inline source citations.
  • Generating Summaries, Study Guides, and Briefing Documents — Hands-on exercise in transforming raw source materials into structured study guides, FAQs, briefing documents, and custom summaries using built-in formatting tools.
  • Creating and Customizing Audio Overviews — Generate a synthetic, two-host podcast discussion based on your sources. Learn how to guide the conversation topic, download the audio, and use it for mobile-friendly learning.
  • Understanding Tool Limits and Best Practices — Explore the constraints of NotebookLM, including source size limits, token caps, and the boundaries of grounded generation to prevent hallucinations in knowledge work.
  • Comprehensive Capstone: Building a Custom Knowledge Assistant — Apply all learned skills in a hands-on scenario: upload a complex set of raw files, generate a briefing document, run complex Q&A, and export an audio overview to solve a mock business problem.

Skills you build

Results are measured against named skills in the OneRange taxonomy of more than 10,000 skills, so a manager sees proficiency per skill rather than a completion tick. This course maps to Working with AI Tools, AI Tool Usage, Summarizing & Synthesizing, Retrieval-Augmented Generation (RAG), Understanding AI Limitations.

  • Working with AI Tools
  • AI Tool Usage
  • Summarizing & Synthesizing
  • Retrieval-Augmented Generation (RAG)
  • Understanding AI Limitations

Who it is for

Researchers, ops, knowledge teams. The material is pitched at beginner level, and takes roughly 90 minutes at a typical pace. Because every session adapts, someone who already knows a topic moves through it quickly instead of sitting through an explanation they do not need.

It sits in the Tool: NotebookLM track of the Vero AI Catalog, and can be assigned to one person, a team, or the whole company.

How it is delivered and assessed

Delivery is conversational and interactive, including guided lab exercises. There is no video to sit through and no slide deck to click past.

Understanding is checked with a lab assessment of 5 items, with a pass mark of 70%.

Administrators can copy this course into their own library and adapt it — edit the outline, change the duration, swap the assessment format, or ground it in internal documentation so answers cite the company's own source material.

Related

Frequently asked questions

How long does this course take?

It runs roughly 90 minutes at a typical pace. Because every session adapts, someone who already knows a topic moves through it quickly instead of sitting through an explanation they do not need.

How is it assigned to a team?

An administrator assigns it from the Vero dashboard to one person, a team, a department or the whole company, and sees progress and results per person and per skill.

Can we customise it with our own documents and terminology?

Yes. Administrators can copy this course into their own library and adapt it — edit the outline, change the duration, swap the assessment format, or ground it in internal documentation so answers cite the company's own source material.

Course code TUL-NLM-101.