Hello human! Welcome to my GitHub.

My name is Quan Tran, a math-oriented data science major at Aalto University. I have a passion for machine learning and a strong foundation in Mathematics, Statistics, and Programming. I am looking for internship and real-world project opportunities to enhance my industry experience.

• Bachelor of Science in Data Science, Aalto University (Expected graduation: Dec 2024)

• Programming language: Scala, C/C++, JavaScript, Rust
• Mathematical programming language: Python, R, Stan, MatLab
• Machine learning libraries: TensorFlow, Scikit-learn
• Data analysis and visualization libraries: Pandas, NumPy, Matplotlib, GGPlot, Bayesplot
• Database management: SQL, PostgreSQL, MySQL
• Experience with Bayesian and Time-series analysis

• Modeling Esophagael Cancer from a Bayesian Perspective - Modeling the probability of developing Esophagael Cancer with Bayesian Linear Logistic Regression method. Achieved an accuracy of 80%.
• Modelling Creditability: A Bayesian Approach - Modelling Creditability of Customers from a German bank with Bayesian Logistic Regression method. Achieved a precision of 81%.
• Predictive Modeling for Sleep Efficiency - Modeling Sleep Effiency with Linear Regression method. Achieved a low Mean-square Error of 0.027.
• Modeling Futures Volatility with BayesARCH - Modeling Gold Futures Volatility with Bayesian ARCH and GARCH model. Achieved a Mean-square Error of 0.386.
• Credit Card Fraud Detection with MDA and LDA - Conducting a Statistical Analysis of Credit Card Fraud with MDA and LDA. Achieved a high Specificity of 0.99 with LDA.

• Vaccine Distribution - A database built to keep track of the different vaccine types, transportation of vaccine batches, treatment plans, staff schedules of vaccination events, and patient data for Corona vaccine distribution and treatment in Finland.

• Wish.com Summer Clothes Sales Performance Analysis - A comprehensive analysis of summer clothes sales performance on Wish.com. The project aims to dive deep into the sales data, revealing consumer preferences, pricing strategies, and the effectiveness of marketing efforts. The goal is to provide actionable insights and data-driven recommendations to enhance sales growth and customer satisfaction in the competitive e-commerce landscape.
• TripAdvisor Hotel Review Analysis - A detailed machine learning analysis of TripAdvisor hotel reviews, aiming to provide actionable insights for business intelligence applications. Utilizing the Weka machine learning toolkit, along with supplementary data processing in R and Python, this analysis addresses two critical scenarios: Predicting hotel ratings based on review texts and Determining the influence level of review authors.

• Application of Multi-attribute Value Theory in Purchasing Plane Ticket - A project aimed to solve a decision problem - deciding which plane ticket to buy - by employing Multi-Attribute Value Theory (MAVT) and value-focused thinking approach.

• DataVizPro - An Interactive Data Dashboard - An advanced interactive dashboard application designed for dynamic data analysis and visualization. The project supports diverse data inputs (CSV, URL, direct input) and facilitates insightful data exploration through various chart types such as scatter plots, column charts, pie charts, and line charts.

• Quýt Lẹt Application - A web application for practicing and managing multiple-choice questions. The application uses a three-tier architecture (client, server, database) and a layered architecture with four layers (views, controllers, services, database). It is built using Deno and Oak and is designed to facilitate learning through repeated practice of course material.
• Shared Shopping Lists Web Application - A web application designed for managing shared shopping lists. Users can create shopping lists, add items to them, mark items as collected, and deactivate shopping lists as needed. The project follows a three-tier architecture (client, server, database) and is organized using a layered architecture with four distinct layers: views, controllers, services, and database.

I am open to opportunities so please feel free to reach out.