Project CodeNet by IBM

Project CodeNet by IBM

A dataset to train AI in understanding and generating code.

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Project CodeNet is a comprehensive dataset designed for artificial intelligence to learn coding. It features around 14 million code samples across more than 55 programming languages, totaling about 500 million lines of code.

This extensive collection serves as a vital resource for researchers and developers aiming to enhance coding practices. By improving AI's ability to interpret and translate code, Project CodeNet makes programming more accessible and efficient.

This dataset supports various applications, such as training AI to generate code, analyzing performance metrics, and assisting in legacy system modernization.

It plays a crucial role in advancing software development and educational programs.


  • Train AI to generate code
  • Improve code translation accuracy
  • Analyze code performance metrics
  • Detect duplicate code snippets
  • Automate code correction processes
  • Facilitate educational coding programs
  • Support software refactoring initiatives
  • Enhance coding competition platforms
  • Assist in legacy system modernization
  • Streamline software development workflows
  • Large dataset with diverse programming languages
  • Facilitates AI learning for coding tasks
  • Rich metadata for better context understanding
  • Helps in automatic code translation
  • Supports software modernization efforts

Coding competitions Legacy modernization Development workflows Code samples Software infrastructure Code management Dataset utilization Software systems Code accessibility Programming languages Coding practices Application development Code documentation Code detection Code efficiency
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