Developing AI-powered applications that integrate Generative AI models with web-based platforms. Working on full-stack development, integrating frontend, backend, and AI models into seamless applications. Optimizing data pipelines and deploying machine learning models in production environments.
August 2024 – October 2024
Internncraft
Data Science Intern (Virtual)
Conducted Coffee Shop Profit Analysis, implementing machine learning models for revenue forecasting. Performed Exploratory Data Analysis (EDA), data preprocessing, feature engineering, and model optimization to improve prediction accuracy. Built interactive dashboards for better decision-making in the real estate and food industries. Built predictive models using machine learning techniques to generate actionable insights. Developed financial forecasts using historical data for better decision-making. Created interactive dashboards and data visualizations using Power BI & Tableau.
My Skills
Core competencies that drive my performance.
Languages
Python99 %
Java94 %
SQL94 %
R97 %
HTML/CSS93 %
Developer Tools
Jupyter Notebook90 %
Google Colab99 %
Git96 %
Github93 %
VS Code90 %
Technologies/Frameworks
Scikit-learn94 %
TensorFlow94 %
Keras93 %
Pandas98 %
NumPy94 %
Matplotlib99 %
Seaborn96 %
Plotly96 %
Power BI91 %
Tableau94 %
MySQL99 %
PostgreSQL96 %
Education
Empowering Creativity through
Expected by May. 2026
Bachelor of Science in Data Science
COMSATS University Islamabad
Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.
My Projects
Customer Experiences: A Tapestry of Happy Moments
Whatsapp AI Agent | n8n
Developed multimodal AI bot for WhatsApp (text, voice, image support)
Datathon 2024 – 2nd Place | Power BI, Data Visualization
Designed an interactive dashboard in 1 hour using Power BI during a live Datathon competition. Analyzed large datasets and presented key insights efficiently under time constraints. Secured 2nd position among multiple participants, demonstrating data storytelling and analytical skills.
Real Estate Price Prediction | Python, Pandas, Scikit-learn, Seaborn
Developed a predictive model to estimate house prices based on real estate datasets of Zameen.com. Performed data preprocessing, feature engineering, and regression modeling to improve accuracy. Visualized price trends and distributions using Matplotlib & Seaborn.
Mental Health Prediction (Frontend + ML) | Fast API, Python, Classification Models
Developed a full-stack ML app using FastAPI to assess anxiety and depression risk. Implemented multiple classification models (KNN, Decision Trees, Naïve Bayes, Random Forest, XGBoost) for accurate predictions.