RAPTOR: Summarization Framework
Description
This course introduces the RAPTOR summarization framework—a structured method for producing accurate and context-aware summaries. Participants explore its application in human and AI workflows across business, research, and communication use cases.
Indicative Duration: 2 training hours
*Duration is adjusted based on the final scope and the target audience.
Scope
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Learning Objectives
Upon completion of the course participants will be able to:
- Understand the components and structure of the RAPTOR summarization framework.
- Apply RAPTOR to extract and condense key information from long-form content.
- Distinguish between extractive and abstractive summarization techniques.
- Use RAPTOR to guide AI systems (e.g., LLMs) in producing focused, high-utility summaries.
- Evaluate and refine summaries for clarity, completeness, and alignment with context or goals.
Target Audience
- Roles: Knowledge Workers, Analysts, Researchers, Content Strategists, Prompt Engineers
- Seniority: Entry to Mid-level professionals working with large volumes of information or designing summarization systems
Prerequisite Knowledge
- Basic understanding of summarization or content distillation concepts
- Familiarity with generative AI tools (e.g., ChatGPT) is useful but not required
Delivery Method
Sessions can be delivered via the following formats:
- Live Online – Interactive virtual sessions via video conferencing
- On-Site – At your organization’s premises
- In-Person – At Code.Hub’s training center
- Hybrid – A combination of online and in-person sessions
The training methodology combines presentations, live demonstrations, hands-on exercises and interactive discussions to ensure participants actively practice AI in realistic work scenarios.
