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thuankhang/README.MD

πŸ‘‹ Hello, I'm Thuan Khang Dinh!

Welcome to my GitHub profile! I’m a Data Science student currently transitioning into my second year, passionate about exploring data and building practical projects. Here’s a bit about me:

πŸ“˜ About Me

  • πŸŽ“ Data Science Student | Currently building my foundation in data analytics, machine learning, and programming.
  • πŸ“ Based in Winnipeg, MB, Canada
  • πŸ‘¨β€πŸ’» Languages & Tools | I have a good understanding of Java, R, Python, SQL, Markdown, Git and Tableau, and am deepening my knowledge in these areas.

πŸ“š Interests & Skills

  • Programming & Algorithms: I enjoy building efficient algorithms and diving into the complexity of data structures.
  • Data Analysis & Visualization: Experienced with R, Python and exploring statistical techniques, plus creating data visualizations to derive insights.

🌱 Currently Learning

  • Advanced Java: Exception handling, recursion, and ADTs.
  • Data Science Techniques: Further statistical analysis, data preprocessing, and visualization (Python, PowerBI).
  • Machine Learning Fundamentals: Exploring basic algorithms and preparing for more advanced ML concepts.

πŸ“« Connect with Me

Thank you for visiting my profile! I’m excited to connect with like-minded individuals and collaborate on projects that make a difference.

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  1. thuankhang.github.io thuankhang.github.io Public

    Forked from AVS1508/My-Alternate-Portfolio-Website

    Portfolio Website using template, generated using Jekyll, Sass, and Gulp.js, to showcase my web presence, rΓ©sumΓ©, story, & featured projects with a Particle.js aligned theme.

    CSS

  2. casestudy-cyclistic-bike-share casestudy-cyclistic-bike-share Public

    In this case study, we will get better understanding about the difference of annual members and casual members using bikes. Our objective is to delve into the Cyclistic historical bike trip data, a…

    HTML

  3. casestudy-sf-bikeshare casestudy-sf-bikeshare Public

    This project aims to evaluate the evolution of the network between 2014 and 2015 and identify critical stations or routes across five cities in the San Francisco Bay Area.

    HTML