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MariiaKrestenko/README.md

Hi, I’m Mariia – Curious About Data, Machine Learning & How Things Really Work 🤖📊

👋 I’m a Data & ML enthusiast who is passionate about bringing data, technology and people together to solve problems and support better decisions.

I’m drawn to data science because real-world data reflects how things actually are. Once you start analysing it, it's not just “doing numbers” but uncovering patterns that can change decisions, workflows and the world around us.

Python Pandas scikit-learn Tableau SQL

Mariia’s Octocat

Focus areas 🚀 Data science | Machine Learning | AI | Data Prep

Tools 💻 Python, Pandas, Numpy, Scikit-learn, Seaborn | SQL | Tableau

Certifications 🎓 Maven Analytics: Data Science in Python, Data Analysis with Python & Pandas | Statistics for Data Analysis | Data Analysis with Python | Coursera: Google Data Analytics Specialization | Google Advanced Data Analytics Specialization

Fellowships / Programs 🌱 Women In Big Data: Emerging Technologists Program | Mentoring Matters


🎯 Open to

  • Entry-level data science or data analyst roles
  • Remote or hybrid positions
  • Collaborating on open source data projects

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  1. bank-customer-churn bank-customer-churn Public

    Clean and prepare customer data for modelling and to build a churn-prediction analysis

    Jupyter Notebook

  2. BeginnerStatisticsPractice BeginnerStatisticsPractice Public

    Practising Linear regression, CI etc.

    Jupyter Notebook

  3. retail-internet-sales-uk retail-internet-sales-uk Public

    Analysing internet sales in UK from 2009 to 2025

    Jupyter Notebook

  4. SpaceMissions SpaceMissions Public

    Use space mission data from 1957-2022 to visualize the history of space travel.

    Jupyter Notebook