TechSheCan Event Series

The TechSheCan Event Series is a sustainability-themed initiative designed to inspire and equip women with essential skills in Data Science, AI, and UX/UI Design. The series consisted of three interactive sessions, combining hands-on workshops and inspiring talks by professionals who transitioned into tech fields.

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📚 Event Overview

🌳 Green Datathons (2 Sessions)

Focused on analyzing global forest trends using the FAO Global Forest Dataset (1990-2020), these datathons aimed to teach foundational data analysis skills.

Key Highlights:

• Speakers:
  • Kehinde Makinde – Data Analyst, transitioned from Information Security
  • Souvenir Okey – Business Analyst, expert in Machine Learning and business insights
• Workshops:
  • Beginner-friendly, code-along sessions using Google Colab
  • Guided use of Python libraries for:
    • Data analysis
    • Cleaning and manipulation
    • Basic prediction tools

Google Colab Link

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🎨 UX/UI Design Hackathon

Aimed at fostering creativity and promoting green solutions, participants designed Personal Carbon Footprint Dashboards in teams and presented their ideas.

Key Highlights:

• Speaker:
  • Sarah Longbottom – Transitioned into UX/UI Design from a non-computing background
• Workshop Topics:
  • Introduction to UI/UX concepts
  • Live Figma demonstration
  • Tips for improving design processes

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📂 Repository Contents

This repository contains all materials and resources from the event series:

📄 Datathon Materials:

• Workshop Notebooks:
  • Beginner-friendly Python notebooks for data cleaning, analysis, and prediction using FAO datasets.
• Dataset Files:
  • FAO Global Forest Dataset (1990-2020).
• Presentation Slides:
  • Slides used during the workshops.

🎨 UX/UI Hackathon Materials:

• Figma Templates:
  • Sample designs for Personal Carbon Footprint Dashboards.
• Guides:
  • Step-by-step instructions on using Figma for beginners.
• Presentation Resources:
  • Overview of UI/UX concepts and design principles.

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🛠️ Tech Stack

• Data Science & AI:
  • Python
  • Google Colab
  • Libraries: Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn
• UX/UI Design:
  • Figma

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License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Thanks to the FAO for providing the Global Forest Insights dataset.
• Special thanks to all contributors who have helped in refining this project.

Happy Data Analysis!