ryo-ngked/data-science-training-2025
Aug 2025 – Sep 2025
2 Months active
Languages Used
Jupyter NotebookMarkdownPythonJSON
Technical Skills
Algorithmic ThinkingBoolean AlgebraBoolean LogicConditional LogicConditional StatementsData Analysis
KhadijahSuhami
PROFILE
Khadijahsuhami
Khadijah Suhaimi developed foundational infrastructure and hands-on learning resources for the ryo-ngked/data-science-training-2025 repository over two months. She established core project scaffolding, imported initial assets, and maintained comprehensive documentation to streamline onboarding and support reproducibility. Her work included creating Jupyter notebooks focused on data analysis with Pandas, covering essential topics such as data types, missing values, grouping, and summary functions. By removing deprecated components and organizing assets, Khadijah enabled a maintainable and scalable environment for future data science experiments. Her contributions demonstrated strong skills in Python, data visualization, and debugging, providing a robust baseline for ongoing project development.
Overall Statistics
Feature vs Bugs
83%Features
Repository Contributions
24Total
Bugs
1
Commits
24
Features
5
Lines of code
84
Activity Months2
Your Network
20 people
Work History
September 2025
3 Commits • 2 Features
Sep 1, 2025September 2025 performance summary for ryo-ngked/data-science-training-2025. Focused on delivering hands-on data science learning resources and establishing the project foundation for scalable future work. Highlights include new Pandas-based practice notebooks and initial scaffolding to enable rapid onboarding and expansion.
3 Commits • 2 Features
Sep 1, 2025September 2025 performance summary for ryo-ngked/data-science-training-2025. Focused on delivering hands-on data science learning resources and establishing the project foundation for scalable future work. Highlights include new Pandas-based practice notebooks and initial scaffolding to enable rapid onboarding and expansion.
September 2025
August 2025
21 Commits • 3 Features
Aug 1, 2025August 2025: Delivered a solid baseline for the data-science-training project by establishing core scaffolding, importing initial assets, and updating documentation, while removing obsolete components. The work reduces onboarding time, improves reproducibility, and sets up a scalable foundation for future experiments and training pipelines.
August 2025
21 Commits • 3 Features
Aug 1, 2025August 2025: Delivered a solid baseline for the data-science-training project by establishing core scaffolding, importing initial assets, and updating documentation, while removing obsolete components. The work reduces onboarding time, improves reproducibility, and sets up a scalable foundation for future experiments and training pipelines.
Activity
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Quality Metrics
Correctness92.4%
Maintainability91.6%
Architecture91.6%
Performance91.6%
AI Usage21.8%
Skills & Technologies
Programming Languages
JSONJupyter NotebookMarkdownPython
Technical Skills
Algorithmic ThinkingBoolean AlgebraBoolean LogicConditional LogicConditional StatementsData AnalysisData ScienceData Science TrainingData TypesData VisualizationDebuggingDictionary UsageDocumentationFunction DefinitionFunctions
Repositories Contributed To
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