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Talieh-Sh/README.md

Hello and welcome to my GitHub page! 👋

Hi there! I'm Talieh and I'm so glad you're here to join in on my data journey. It all started 7 years ago in a sales department, where I got to grips with creating reports and dashboards using Excel, VBA, and QlikView. My curiosity soon led me to the world of marketing analytics, where I enjoyed digging into campaign results and brand health. This experience was a springboard into a business analyst role, where I used Power BI to make life easier for retail sales teams with better reporting tools. More recently, I've been back in the data analyst seat, this time in education, crafting systems that help managers and their teams save precious time. In the last ten months, I've been leveling up my skills in Python, SQL, and Machine Learning through Monash University's Data Analysis Bootcamp, and I'm building cool projects along the way. I'm excited about what's next and really appreciate you stopping by to share in this journey with me. Cheers to more learning and growing together!

  • 🔭 I’m currently working on some data analyzing projects.
  • 🌱 I’m currently learning more about Machine Learning and cloud services.
  • 📫 How to reach me: You can email me at talieh.sh.mail@gmail.com.
  • 😄 Pronouns: Her/Hers.

🚀  Some Tools I Have Used and Learned

Here are some of the tools and technologies that I have used and learned:

  • Python
  • SQL
  • PostgreSQL
  • Power Bi
  • Tableau
  • MongoDB
  • HTML/CSS
  • Excel
  • Visual Basic

Pinned Loading

  1. falconpunch082/la-crime-visualiser falconpunch082/la-crime-visualiser Public

    Monash University Data Analytics Bootcamp Project 3 by Group 5 (Michael, Talieh, Wassim, Nicholas)

    JavaScript 1 1

  2. python-api-challenge python-api-challenge Public

    Jupyter Notebook

  3. DataVisualisation-challenge DataVisualisation-challenge Public

    Jupyter Notebook

  4. Project1Group1 Project1Group1 Public

    The project explored Melbourne's public transport use and housing sales. Python tools visualized data on transport footfall and housing by council areas. Sources included PTV for transport data and…

    Jupyter Notebook

  5. belly-button-challenge belly-button-challenge Public

    JavaScript

  6. Bank_Churn_Project Bank_Churn_Project Public

    Project uses ML models (XGBoost, Regression, RandomForest, Neural Networks) to predict bank customer churn. XGBoost led with 86.73% accuracy. Utilized Tableau for visualization, hosted online via …

    Jupyter Notebook