SKILLS

Programming Languages

• Python

• C

• Java

• SQL(Basic)

Data Science

• Data Cleaning & Preprocessing

• Exploratory Data Analysis (EDA)

• Unsupervised Machine Learning (K-Means Clustering)

• Model Evaluation (Elbow Method, Silhouette Score, Inertia, r2 score, MAE, Precision, Recall, f1-score )

• Data Visualization (Matplotlib, Seaborn)

• Feature Selection (basic)

• Python for Data Science

• Feature Engineering (Basic)

Tools and Technologies

• Jupyter Notebook

• Git and Github

• VS Code

Soft Skills

• Problem Solving

• Critical Thinking

• Consistency and Self-Learning

WORK EXPERIENCE

Data Science Projects (Self-Directed)

Remote | 2025-Present

• Built end-to-end machine learning projects including house price prediction, predicting survivors on the Titanic and customer churn prediction, applying regression and classification techniques.

• Performed full data science workflow: data cleaning, exploratory data analysis (EDA), feature engineering, and model evaluation.

• Compared model performance using metrics such as accuracy and error rates to improve predictions.

• Applied feature selection techniques to identify key variables influencing outcomes.

• Documented and structured projects for reproducibility and portfolio presentation

Academic / Personal Projects | 2024 – Present

• Developed multiple programming exercises and class-based projects to strengthen core programming skills in Python, Java, and C.

• Built a Git-like system (UGit project) in Python simulating version control functionality such as commit tracking and repository management.

• Practiced object-oriented programming (OOP), data structures, and algorithm design through structured assignments

• Improved debugging, code organization, and software design principles through continuous practice

Workshop Certification(s)