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Guided instruction computational notebooks for students in AI/ML programs without formal training in relational calculus and algebra to learn through computational notebooks:


Guided instruction computational notebooks for students in AI/ML programs without formal training in relational calculus and algebra to learn through computational notebooks:
Wolfram Development Platform - Provides free access to Wolfram computational capabilities through APIs and notebooks. Students could use Wolfram notebooks to interactively learn relational math concepts.
Google Colab - Free cloud-based Jupyter notebooks. Students could create notebooks that guide them through relational math topics using Python/pandas, visualization libraries, etc.
Microsoft Azure Notebooks - Free cloud-based Jupyter notebooks with Azure integration. Similar to Google Colab.
Jupyter Notebook with Sympy - Open source computational notebooks using the Sympy symbolic math library for Python. Could create customized notebooks on relational math.
MATLAB Online - Browser-based MATLAB notebooks. MATLAB has strong relational math capabilities via sets, relations, etc. Free tier has limitations.
SageMath - Open-source computational notebook using Python. Has features for mathematical concepts including relations and sets.
Hugging Face Spaces - Could create notebooks teaching relational math concepts then apply via Hugging Face transformers and models.
The key criteria would likely be ease of use, ability to create highly interactive and visualization-driven notebooks, available mathematical capabilities, and integration with languages/libraries used in the AI/ML coursework (Python, pandas, etc.). A blend of a few options may provide the most flexibility.
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