Course Outline

Introduction to NotebookLM for Research

  • Core capabilities and limitations
  • Navigating the NotebookLM workspace
  • Understanding research-oriented AI interactions

Managing Research Sources

  • Importing documents and datasets
  • Organizing sources effectively
  • Linking related materials for multi-source analysis

Advanced Synthesis Techniques

  • Generating summaries across multiple documents
  • Extracting key points and themes
  • Identifying patterns and relationships

Citation and Reference Management

  • Automated citation extraction
  • Structuring bibliographic data
  • Exporting citations for academic writing

AI-Assisted Knowledge Structuring

  • Building conceptual maps with AI
  • Organizing insights into frameworks
  • Iterative refinement of research structures

Report and Output Generation

  • Creating research briefs and summaries
  • Generating comparison matrices and structured insights
  • Preparing materials for publication or presentation

Collaborative Research Workflows

  • Sharing notebooks and insights
  • Collective synthesis with teams
  • Maintaining consistency across shared research spaces

Best Practices for Research Governance

  • Ensuring data accuracy and source integrity
  • Developing reusable research templates
  • Establishing organizational knowledge standards

Summary and Next Steps

Requirements

  • An understanding of digital research workflows
  • Experience with academic or professional literature review processes
  • General familiarity with cloud-based productivity tools

Audience

  • Researchers who wish to enhance synthesis and analysis workflows
  • Academics who wish to streamline citation management and source organization
  • Knowledge workers who wish to optimize large-scale information handling
 14 Hours

Number of participants


Price per participant

Provisional Upcoming Courses (Contact Us For More Information)

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