Dynamic runtime environment creation for machine learning project execution such that resources are used only during class and incur no cost when no class is running.
Built autoscaling of kernels as per number of concurrent projects running in any class or multiple classes at the same time such that the code execution is not hampered due to sudden load
Elaborate system to onboard students and build projects on a drag and drop block system for building ML models and tweaking parameters based on algorithm being used.
Extremely dynamic design for various sections and lengthy content without any fixed pattern for templatisation
Single template for both English and Arabic versions, saving time and effort
Over 100 pages of content in each English and Arabic delivered within 3 weeks

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