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https://github.com/tinashemillicent/portfolio

This repository serves as a central portfolio for my professional journey as an Associate Data Analyst and IT Professional. It highlights selected projects, technical skills, certifications, and writing β€” all reflecting my interest in data, analytics, and impactful problem-solving.
https://github.com/tinashemillicent/portfolio

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This repository serves as a central portfolio for my professional journey as an Associate Data Analyst and IT Professional. It highlights selected projects, technical skills, certifications, and writing β€” all reflecting my interest in data, analytics, and impactful problem-solving.

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Millicent's Portfolio


Associate Data Analyst & IT Professional

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## πŸ“« Contact

- πŸ“§ Email: [tinashesefaidiga@gmail.com](mailto:tinashesefaidiga@gmail.com)
- 🌐 Blog: [Medium | tinashemillicent](https://medium.com/@tinashemillicent)
- 🌐 Persona Blog: [Substack | tinashemillicent](https://tinashemillicent.substack.com)
- πŸ’Ό LinkedIn: [Millicent Sefaidiga](https://linkedin.com/in/millicentsefaidiga)

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## πŸ‘‹ Welcome

I’m **Tinashe Millicent**, a data-driven professional with a passion for turning information into insight. With a background in IT and data analysis, I enjoy solving real-world problems using structured thinking, analytics, and machine learning tools.

In my free time, you'll find me relaxing with anime or diving into a new book β€” always learning, always exploring.

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## πŸ’Ό Selected Projects

| Project | Description | Tools |
|--------|-------------|-------|
| [Breast Cancer Prediction](https://github.com/tinashemillicent/Breast-Cancer-Prediction)) | A classification task aimed at predicting the diagnosis of a breast mass as either malignant or benign. | `Python`, `Pandas`, `MatPlotlib`, `Seaborn` |
| [Warranty Claims Fraud Detection](https://github.com/tinashemillicent/Warranty-Claims-Fraud-Detection)) | This project focuses on identifying potential fraudulent warranty claims by building and evaluating machine learning models. Detecting fraud in warranty claims helps companies reduce financial losses and maintain trust with legitimate customers. | `Python`, `Pandas`, `MatPlotlib`, `Seaborn`,`Logistic regression`, `decision tree classifier`, `random forest` |
| [Salary Prediction](https://github.com/tinashemillicent/Salary-Prediction)) | The aim of this project to predict the salary of individuals from varied countries and races based on their demographics such as occupation, age, gender, experience, education, etc. The dataset is taken from Kaggle. The dataset has 6704 rows and 9 columns. The dataset has 8 independent variables and 1 target variable i.e Salary | `Python`, `Pandas`, `MatPlotlib`, `Seaborn`, `decision tree regressor`, `random forest regressor` |

> πŸ“Œ Each project is housed in its own repository. Click the links to explore the code, reports, and visuals.

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## 🧠 Skills Snapshot

- **Languages & Tools:** Python, SQL, Excel, Power BI, Tableau
- **Libraries:** pandas, NumPy, scikit-learn, Matplotlib, Seaborn
- **Other:** Git, Jupyter, VSCode, Bash, Agile workflows

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## πŸ“œ Courses & Certifications

- Google Foundations of Business Intelligence
- Google Foundations of Data Science
- IBM Introduction to Data Analytics
- Google System Administration and IT Infrastructure
- Google The Path to Insights_Data Models and Pipelines
- Google Decisions, Dashboards an reports
- LinkedIn Learning: Artificial Intelligence Foundation: Machine Learning
- LinkedIn Learning: Introduction to Web design and Development
- LinkedIn Learning: Java Object Oriented Programming
- LinkedIn Learning: Ethical hacking: system hacking

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## πŸ“ Blog & Writing

I share thoughts on data, tech, and learning on my [blog](https://medium.com/@tinashemillicent).

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## πŸ“« Contact

- πŸ“§ Email: [tinashesefaidiga@gmail.com](mailto:tinashesefaidiga@gmail.com)
- 🌐 Blog: [Medium | tinashemillicent](https://medium.com/@tinashemillicent)
- 🌐 Persona Blog: [Substack | tinashemillicent](https://tinashemillicent.substack.com)
- πŸ’Ό LinkedIn: [Millicent Sefaidiga](https://linkedin.com/in/millicentsefaidiga)

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Thank you for visiting β€” let’s connect and build something amazing.