[Korea Polytechnics Gwangju Campus] Building an Integrated Platform for AI Practice and Course Operations

To run its AI Convergence department and strengthen practice-oriented education, Korea Polytechnics Gwangju Campus adopted an integrated platform where AI development and learning take place in one environment.

An Integrated Development and Learning Environment for AI Convergence Education

With the launch of its AI Convergence department, Korea Polytechnics Gwangju Campus needed an educational environment that seamlessly connects the course curriculum with hands-on practice. It also required a foundation to systematically manage AI development tools and libraries and respond immediately to GPU expansion.

Integrated Support for AI Course Operations and Lab Environments

The key challenge was to efficiently support everything from curriculum operations to AI practice, development tool management, and GPU use on a single platform.

  • AI curriculum support: Consulting on AI education and practice for running courses

  • Integrated development and learning environment: An environment for both AI development and course content learning on one platform

  • Tool and resource management: An environment that flexibly handles AI library and framework updates and GPU expansion

Providing an Integrated AI Development and Learning Platform with Operations Support

With Cheetah, we provided an integrated environment for both AI development and learning, along with curriculum consulting, course content, version-specific development tools, and GPU expansion capabilities.

  • AI curriculum consulting: Supported planning and running the course curriculum for the AI track

  • Integrated development and learning environment: Course content and AI development environments provided together on the platform

  • Flexible tool and GPU operations: Version-specific libraries and frameworks with GPU expansion capabilities

More Efficient AI Practice and Easier Operations

Korea Polytechnics Gwangju Campus now has an environment for AI development and learning on a single platform, making it easier to run AI practice across various courses and departments. Administrators can operate infrastructure resources efficiently, and both students and the school can focus more on education and projects themselves.

  • More efficient lab operations: Easy AI environment setup across various tracks and departments

  • Better connection between learning and practice: Integrated course content and lab environments for smooth course operations

  • Easier management: More efficient management of GPU and infrastructure resources

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