
María León developed and maintained course materials for the alexanderquispe/Diplomado_PUCP repository, focusing on Python fundamentals and data analysis workflows. She created and updated Jupyter notebooks for lectures and assignments, integrating hands-on exercises using Python, pandas, and NumPy to support student learning. Her work included cleaning up outdated content, improving file organization, and documenting Git workflows to streamline collaboration. By consolidating course notebooks and refining metadata, María enhanced the maintainability and deployment readiness of the material. The depth of her contributions is reflected in the coherent, reusable notebook suite that supports both instructors and students in a reproducible environment.

September 2025 achieved feature delivery and material readiness for Diplomado_PUCP. Delivered the Course Notebook Suite: Data Analysis and Python Loops (Lecture 2-3), including notebooks for lectures, assignments, and solutions, focused on pandas data analysis, data loading/cleaning/merging, basic statistics, and Python loop constructs across data structures. Performed maintenance cleanups such as folder creation, file renames, and metadata updates to support course materials and future reuse. The commit history shows steady iteration toward a stable release, with multiple commits culminating in a coherent, deployable package. Overall impact: improved course material readiness, streamlined instructor/student workflows, and demonstrated strong Python/pandas skills, Jupyter notebook discipline, and Git-based collaboration.
September 2025 achieved feature delivery and material readiness for Diplomado_PUCP. Delivered the Course Notebook Suite: Data Analysis and Python Loops (Lecture 2-3), including notebooks for lectures, assignments, and solutions, focused on pandas data analysis, data loading/cleaning/merging, basic statistics, and Python loop constructs across data structures. Performed maintenance cleanups such as folder creation, file renames, and metadata updates to support course materials and future reuse. The commit history shows steady iteration toward a stable release, with multiple commits culminating in a coherent, deployable package. Overall impact: improved course material readiness, streamlined instructor/student workflows, and demonstrated strong Python/pandas skills, Jupyter notebook discipline, and Git-based collaboration.
August 2025: Delivered significant course content updates for alexanderquispe/Diplomado_PUCP focused on Python Fundamentals. Finalized Assignment 1 with student contributions and hands-on exercises (NumPy/Pandas), and cleaned up notebook materials across lectures. Introduced clearer Git workflow explanations and improved content accuracy, while removing outdated notebooks to reduce technical debt. Result: enhanced learner experience, faster onboarding, and a maintainable, reproducible notebook suite.
August 2025: Delivered significant course content updates for alexanderquispe/Diplomado_PUCP focused on Python Fundamentals. Finalized Assignment 1 with student contributions and hands-on exercises (NumPy/Pandas), and cleaned up notebook materials across lectures. Introduced clearer Git workflow explanations and improved content accuracy, while removing outdated notebooks to reduce technical debt. Result: enhanced learner experience, faster onboarding, and a maintainable, reproducible notebook suite.
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