ryo-ngked/data-science-training-2025
Aug 2025 – Sep 2025
2 Months active
Languages Used
JSONJupyter NotebookMarkdownPython
Technical Skills
Algorithmic ThinkingBasic ArithmeticBoolean LogicBooleansConditional StatementsConditionals
WYBeh
PROFILE
Wybeh
Developed and maintained core data science training materials in the ryo-ngked/data-science-training-2025 repository over a two-month period, focusing on building a comprehensive Python Learning Notebooks Library and a set of Data Cleaning Course Notebooks. Leveraged Python, Jupyter Notebooks, and Pandas to create beginner-friendly exercises covering topics such as arithmetic, variables, data types, conditionals, data cleaning, and visualization. Emphasized hands-on learning by implementing practical exercises for data manipulation, missing values, and date parsing. Maintained curriculum relevance by removing deprecated content and enhancing documentation, supporting both onboarding and self-paced learning for new data science students without introducing reported bugs.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
22Total
Bugs
0
Commits
22
Features
3
Lines of code
3,144
Activity Months2
Your Network
20 peopleWork History
September 2025
2 Commits • 1 Features
Sep 1, 2025Concise monthly summary for 2025-09: Delivered Data Cleaning Course Notebooks as part of the ryo-ngked/data-science-training-2025 repo. Implemented practical data cleaning exercises covering data types, missing values, renaming, combining, scaling/normalization, character encodings, and date parsing. Two notebook uploads were added via commits 5d733b339687cf2cc468fb1eb89ba219c9ff8e33 and 0efe61a9639ca0b6366057a76b7f8ac6c4e7957e to implement the curriculum. No major bugs reported this month. This work strengthens the data-prep curriculum, enabling hands-on practice and faster onboarding for learners. Technologies demonstrated include Jupyter notebooks, Python data manipulation, and Git version control.
2 Commits • 1 Features
Sep 1, 2025Concise monthly summary for 2025-09: Delivered Data Cleaning Course Notebooks as part of the ryo-ngked/data-science-training-2025 repo. Implemented practical data cleaning exercises covering data types, missing values, renaming, combining, scaling/normalization, character encodings, and date parsing. Two notebook uploads were added via commits 5d733b339687cf2cc468fb1eb89ba219c9ff8e33 and 0efe61a9639ca0b6366057a76b7f8ac6c4e7957e to implement the curriculum. No major bugs reported this month. This work strengthens the data-prep curriculum, enabling hands-on practice and faster onboarding for learners. Technologies demonstrated include Jupyter notebooks, Python data manipulation, and Git version control.
September 2025
August 2025
20 Commits • 2 Features
Aug 1, 2025August 2025 (2025-08) focused on delivering and maintaining core data-science training content in ryo-ngked/data-science-training-2025. Key deliverables included launching a broad Python Learning Notebooks Library (WY Beh Release) to support an introductory data science course, and cleaning up learning materials by removing deprecated exercises to keep content current. The month also encompassed release-readiness and documentation improvements to bolster onboarding and self-paced learning.
August 2025
20 Commits • 2 Features
Aug 1, 2025August 2025 (2025-08) focused on delivering and maintaining core data-science training content in ryo-ngked/data-science-training-2025. Key deliverables included launching a broad Python Learning Notebooks Library (WY Beh Release) to support an introductory data science course, and cleaning up learning materials by removing deprecated exercises to keep content current. The month also encompassed release-readiness and documentation improvements to bolster onboarding and self-paced learning.
Activity
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Quality Metrics
Correctness98.8%
Maintainability98.2%
Architecture97.2%
Performance97.2%
AI Usage22.8%
Skills & Technologies
Programming Languages
JSONJupyter NotebookMarkdownPython
Technical Skills
Algorithmic ThinkingBasic ArithmeticBoolean LogicBooleansCharacter EncodingConditional StatementsConditionalsData AnalysisData Analysis FundamentalsData CleaningData ManipulationData ScienceData TypesData VisualizationData Visualization (implied by notebook format)
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