Python ate my Homework!
summary
A live notebook demonstrates using SymPy and Jupyter to replace handwritten math with code: using SymPy factorint to factor integers, unevaluated expressions and EQ/display to show stepwise working, and the built‑in sum_of_squares and solve/diff/plot tools for discrete, calculus and 3D optimization problems. The demo builds a calculator that prints LaTeX, exports the notebook to HTML/PDF, completes a sample assignment in about twenty minutes and computes concrete results like U2 ≈ 7000 U1 ≈ 4000 and a maximum ≈ 1,000,000.
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chapters (25)
- 0:00Introduction
- 0:48Why Python for math
- 3:19Setting up math demo
- 6:14Prime factors with SymPy
- 7:17Adding working steps
- 8:43Visualizing math with LaTeX
- 10:52Submitting first problem
- 11:58Calculus intersection problem
- 13:23Equation display with SymPy
- 14:27Working for intersection points
- 15:31Quadratic formula and roots
- 17:41Finding curve's vertex
- 18:48Plotting curve with SymPy
- 19:09Extending to 3D
- 20:343D optimization with SymPy
- 22:18Solving for optimal profit
- 23:43SymPy contributions
- 24:47Exporting notebooks
- 25:31Resources and call to action
- 26:02Q&A
- 27:31AI tool comparison
- 28:59Practicality vs submission
- 30:25Handling extreme quadratics
- 32:34Future of symbolic math
- 33:39Summary
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