Data Structures with Python
summary
Course redesign pairs C and Python comparisons and claims a drop from 85% to 12% failure rate by shifting labs and assignments into Python while keeping C for low‑level contrast. Concrete classroom artifacts include short Python word‑count and sorting projects, a graph theory solver and a comparison benchmark where native Python sorts win; author quotes a code size contrast of 20 lines vs 500 lines. Assessment reports sustained student improvement and contest wins.
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chapters (9)
- 0:00Introduction
- 0:14Challenges with C
- 2:10Transitioning to Python
- 4:31Teaching methodology
- 7:48Code comparisons
- 12:44Algorithm implementations
- 17:37Exercises and projects
- 22:05Practical project examples
- 26:02Conclusion
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