Publication | Closed Access
Notes on Using Google Colaboratory in AI Education
61
Citations
3
References
2020
Year
Unknown Venue
Artificial IntelligenceAi ArchitectureIntelligent Tutoring SystemsEngineeringMachine LearningData ScienceDeep Reinforcement LearningGoogle ColaboratoryTeaching AiEducationLearning AnalyticsComputer ScienceIntelligent SystemsRobot LearningJupyter NotebooksUndergraduate Artificial IntelligenceAi Education
We discuss our experiences using Google Colaboratory (Colab), a hosted version of Jupyter Notebooks, in undergraduate artificial intelligence (AI) courses at two universities. Colab was designed for AI and data science researchers to share reproducible experiments and explanations of techniques, but we have also found it well suited to classroom use. The primary benefit is that it provides students computational resources sufficient to run modern AI techniques interactively, and avoids students needing to separately configure software packages and dependencies, since they can run notebooks shared by the instructor. We briefly outline two of our notebooks, for teaching deep learning with Tensorflow, and reinforcement learning with OpenAI Gym.
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