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
WY Beh developed and maintained core data science training materials in the ryo-ngked/data-science-training-2025 repository, focusing on building a comprehensive library of beginner-friendly Jupyter notebooks. Their work included designing Python-based exercises covering arithmetic, variables, data types, conditionals, functions, and data visualization with Pandas and Matplotlib, supporting an introductory curriculum. WY Beh also implemented practical data cleaning notebooks, addressing data types, missing values, normalization, character encoding, and date parsing to enhance hands-on learning. Throughout the two-month period, they prioritized curriculum relevance by removing deprecated content and improving documentation, demonstrating consistent delivery and depth in both content creation and repository maintenance.
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 people
Work 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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