chsharrison/Sci_comp_F24
Oct 2024 – Dec 2024
3 Months active
Languages Used
Jupyter NotebookMarkdownPython
Technical Skills
Data AnalysisFizzBuzz ProblemJupyter NotebookNumPyPandasPython Programming
punchvic
PROFILE
Punchvic
Over a three-month period, contributed a suite of nine features to the chsharrison/Sci_comp_F24 repository, focusing on reproducible Jupyter notebooks for scientific computing and data science education. Developed instructional labs covering topics such as FizzBuzz, NumPy and Pandas exercises, file transfer workflows to HPC systems, time series analysis, and environmental data visualization. Implemented computational modeling with differential equations and machine learning classification using Python, scikit-learn, and matplotlib. Emphasized clear documentation, onboarding readiness, and asset management to support both self-guided learning and project reporting. Maintained repository stability throughout, with no major bugs reported, demonstrating depth in technical execution and educational design.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
13Total
Bugs
0
Commits
13
Features
9
Lines of code
10,369
Activity Months3
Your Network
9 peopleWork History
December 2024
5 Commits • 5 Features
Dec 1, 2024December 2024 delivered a cohesive set of reproducible notebooks in the Sci_comp_F24 project, focusing on practical data science skills and computational modeling. Key work established ready-to-use resources for learning, experimentation, and reporting, with an emphasis on clear documentation and accessible demonstrations of modeling, ML, data wrangling, and environmental data analysis. The work supports onboarding, self-guided learning, and evidence-based project reporting while strengthening core technical capabilities.
5 Commits • 5 Features
Dec 1, 2024December 2024 delivered a cohesive set of reproducible notebooks in the Sci_comp_F24 project, focusing on practical data science skills and computational modeling. Key work established ready-to-use resources for learning, experimentation, and reporting, with an emphasis on clear documentation and accessible demonstrations of modeling, ML, data wrangling, and environmental data analysis. The work supports onboarding, self-guided learning, and evidence-based project reporting while strengthening core technical capabilities.
December 2024
November 2024
3 Commits • 1 Features
Nov 1, 2024Concise monthly summary for 2024-11 focused on delivering practical data science lab infrastructure and HPC workflow support within the Sci_comp_F24 project. The month centered on creating ready-to-use notebooks for Lab 11.x (statistics, file transfer to LSU HPC, and time series analysis), plus solidifying the approach through initial commits and clear documentation.
November 2024
3 Commits • 1 Features
Nov 1, 2024Concise monthly summary for 2024-11 focused on delivering practical data science lab infrastructure and HPC workflow support within the Sci_comp_F24 project. The month centered on creating ready-to-use notebooks for Lab 11.x (statistics, file transfer to LSU HPC, and time series analysis), plus solidifying the approach through initial commits and clear documentation.
October 2024
5 Commits • 3 Features
Oct 1, 2024Concise monthly summary for 2024-10: Delivered three major features in chsharrison/Sci_comp_F24, plus onboarding assets. Key notebooks include a FizzBuzz Lab Notebook and a Scientific Computing lab notebook with NumPy/Pandas exercises, along with essential artifacts for Zhenwei Wu (CV, final proposal, bib screenshot). No major bugs reported; maintained stability. Business impact includes enhanced learning resources, reproducibility, and onboarding readiness, demonstrating strong notebook-based teaching artifacts and asset management.
5 Commits • 3 Features
Oct 1, 2024Concise monthly summary for 2024-10: Delivered three major features in chsharrison/Sci_comp_F24, plus onboarding assets. Key notebooks include a FizzBuzz Lab Notebook and a Scientific Computing lab notebook with NumPy/Pandas exercises, along with essential artifacts for Zhenwei Wu (CV, final proposal, bib screenshot). No major bugs reported; maintained stability. Business impact includes enhanced learning resources, reproducibility, and onboarding readiness, demonstrating strong notebook-based teaching artifacts and asset management.
October 2024
Activity
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Quality Metrics
Correctness90.8%
Maintainability90.8%
Architecture87.6%
Performance83.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookMarkdownPython
Technical Skills
Command Line InterfaceData AnalysisData ScienceData VisualizationDifferential EquationsFile TransferFizzBuzz ProblemHPC UsageJupyter NotebookJupyter NotebooksMachine LearningMatplotlibNumPyNumerical MethodsPandas
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