alexanderquispe/Diplomado_PUCP
Aug 2025 – Sep 2025
2 Months active
Languages Used
JSONJupyter NotebookMarkdownPythonSQL
Technical Skills
Data AnalysisData StructuresDocumentationJupyter Notebook ManagementJupyter NotebooksNumPy
ulisesrodas
PROFILE
Ulisesrodas
Contributed to the alexanderquispe/Diplomado_PUCP repository by enhancing educational Jupyter notebooks focused on Python programming and data analysis. Over two months, delivered four new features that expanded instructional content, including improved examples, control flow demonstrations, and introductory object-oriented programming concepts. Applied Python, NumPy, and pandas to create robust, learner-friendly materials, refining input handling and data workflows for greater reliability. Emphasized clear documentation and maintainable code, updating Markdown references and notebook explanations to support both students and future contributors. The work prioritized clarity, actionable guidance, and efficient onboarding, resulting in richer course materials and more effective learning outcomes for the cohort.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
12Total
Bugs
0
Commits
12
Features
4
Lines of code
1,244
Activity Months2
Your Network
40 peopleWork History
September 2025
4 Commits • 2 Features
Sep 1, 2025September 2025 performance summary for alexanderquispe/Diplomado_PUCP: Delivered feature enhancements and input robustness improvements to the educational Jupyter notebooks used for data analysis and Python basics. Key work included: enhanced notebook content with expanded coverage for identity operators, nested if statements, NumPy-based loops, pandas data loading, data type conversions, and vectorized operations; addition of control flow and introductory OOP concepts via new code cells. Also improved input loop handling to ignore negative numbers, with refined prompts and updated test data to prevent unintended breaks. Impact includes richer instructional content, more reliable notebook execution, and improved student learning outcomes. Technologies demonstrated include Python, NumPy, pandas, and Jupyter Notebooks. Commit activity: updates across group_09_assignment2_2025.ipynb and group_09_assignment3_2025.ipynb (multiple commits).
4 Commits • 2 Features
Sep 1, 2025September 2025 performance summary for alexanderquispe/Diplomado_PUCP: Delivered feature enhancements and input robustness improvements to the educational Jupyter notebooks used for data analysis and Python basics. Key work included: enhanced notebook content with expanded coverage for identity operators, nested if statements, NumPy-based loops, pandas data loading, data type conversions, and vectorized operations; addition of control flow and introductory OOP concepts via new code cells. Also improved input loop handling to ignore negative numbers, with refined prompts and updated test data to prevent unintended breaks. Impact includes richer instructional content, more reliable notebook execution, and improved student learning outcomes. Technologies demonstrated include Python, NumPy, pandas, and Jupyter Notebooks. Commit activity: updates across group_09_assignment2_2025.ipynb and group_09_assignment3_2025.ipynb (multiple commits).
September 2025
August 2025
8 Commits • 2 Features
Aug 1, 2025August 2025 monthly summary for Diplomado_PUCP repository. Focused on elevating course materials and documentation to improve learning outcomes and maintainability. Delivered notebook content enhancements and expanded reference material in Markdown, aligning with the curriculum and cohort needs. The work emphasizes clear, actionable content and efficient collaboration for faster onboarding of future contributors.
August 2025
8 Commits • 2 Features
Aug 1, 2025August 2025 monthly summary for Diplomado_PUCP repository. Focused on elevating course materials and documentation to improve learning outcomes and maintainability. Delivered notebook content enhancements and expanded reference material in Markdown, aligning with the curriculum and cohort needs. The work emphasizes clear, actionable content and efficient collaboration for faster onboarding of future contributors.
Activity
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Quality Metrics
Correctness88.4%
Maintainability86.6%
Architecture80.0%
Performance80.0%
AI Usage21.6%
Skills & Technologies
Programming Languages
JSONJupyter NotebookMarkdownPythonSQL
Technical Skills
ClassesControl FlowData AnalysisData StructuresDocumentationFunctionsJupyter NotebookJupyter Notebook ManagementJupyter NotebooksNumPyObject-Oriented ProgrammingPandasPythonPython Programming
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