2026 (Present)
Data Science Specialization
Selected for the specialized Data Science track in my 3rd year at SLIIT. Focused on advanced statistical modeling, machine learning algorithms, and big data technologies.
About Me
Sushan Tharuka
Data Science Undergraduate at SLIIT
I am a third-year IT undergraduate at SLIIT specializing in Data Science, currently building a strong foundation in statistics, machine learning, and software development. My passion lies in turning raw data into clear insights and practical solutions—whether through data visualization, predictive models, or clean analytical dashboards.
Over the past two years, I have worked on various academic and personal projects involving data cleaning, exploratory analysis, and ML modeling, continuously improving my skills in Python, SQL, and modern data tools. My goal is to grow into a data professional who can collaborate with teams to solve real-world problems in areas like business analytics, finance, and product optimization.
Outside of coursework, I enjoy experimenting with new libraries, following industry best practices, and learning how to communicate technical results to non-technical stakeholders. I am currently focused on strengthening my portfolio with real-world datasets, collaborative projects, and internships in the data science field.
Key Skills
Core Data
Python
Pandas
Scikit-Learn
Data Visualization
Machine Learning
Tools & DB
MySQL
MongoDB
Power BI
Git / GitHub
React / Node.js
2026(Present)
Academic Data Projects
Worked on exploratory analysis & cleaning for course and personal datasets.
2024
IT & Development Foundation
Built a strong software engineering background (Web & Mobile) over two years. This technical foundation now allows me to build custom dashboards and deploy ML models effectively.
My Skills
A selection of projects that demonstrate my skills in data analysis, machine learning, and problem-solving, applying statistical and computational techniques to real-world datasets.
85%
HTML
80%
CSS
60%
JavaScript
70%
React
90%
Tailwind CSS
65%
PHP
55%
Node.js
70%
MySQL
60%
MongoDB
75%
Kotlin
80%
Git
80%
VS Code
85%
Figma
Featured Projects
A showcase of my development journey through various projects that demonstrate my technical skills and problem-solving abilities, built over 2 years of learning and 6 months of hands-on experience.
My Experience
Data Science undergraduate focused on practical analysis, machine learning, and clear communication of insights.
Undergraduate
Data Science Undergraduate
Building a strong foundation in statistics, data wrangling, and ML. Turning raw data into clear, actionable insights through clean code and effective visuals.
Key Achievements:
- Completed EDA dashboards using Python, Pandas, NumPy and Matplotlib.
- Built baseline ML models (classification/regression) with scikit‑learn.
- Prepared datasets: cleaning, feature engineering, and train/test evaluation.
- Presented insights with concise visuals and simple narratives.
PythonPandasNumPyscikit‑learnSQLMatplotlibSeaborn
Self‑Learning
Student Data Projects
Hands‑on learning through real datasets and small analytics projects with a focus on trustworthy results and readable code.
Key Achievements:
- Kaggle notebooks exploring cleaning, visualization, and model baselines.
- Built simple ETL scripts for CSV/JSON APIs and local storage.
- Versioned projects with Git/GitHub and wrote clear READMEs.
- Improved communication by summarizing findings for non‑technical peers.
JupyterKaggleSeabornPower BIGitGitHub
Contact Me
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